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Savarese, Paul Tenzing. "New design comparison criteria in Taguchi's robust parameter design." Diss., This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-06062008-171200/.
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Lehman, Jeffrey S. "Sequential Design of Computer Experiments for Robust Parameter Design." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1027963706.
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Lehman, Jeffrey Scott. "Sequential design of computer experiments for robust parameter design." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486463321623652.
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Lee, Sang Heon. "Efficient design and optimization of robust parameter experiments." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/24328.
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Min, Jun Young. "Off-line quality control by robust parameter design." Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/597.
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Dasgupta, Tirthankar. "Robust Parameter Design for Automatically Controlled Systems and Nanostructure Synthesis." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16300.
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This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures.
In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored.
To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.
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Muhler, Michael Ludwig. "Robust control system design by mapping specifications into parameter spaces." [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=984575332.
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Bhagawat, Pankaj. "Design of a robust parameter estimator for nominally Laplacian noise." Texas A&M University, 2003. http://hdl.handle.net/1969/107.
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How, Jonathan P. "Robust control design with real parameter uncertainty using absolute stability." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12538.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1993.<br>GRSN 640480<br>Includes bibliographical references (p. 185-198).<br>by Jonathan P. How.<br>Ph.D.
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Kim, Yoon G. "A response surface approach to data analysis in robust parameter design." Diss., Virginia Tech, 1992. http://hdl.handle.net/10919/38627.
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It has become obvious that combined arrays and a response surface approach can be effective tools in our quest to reduce (process) variability. An important aspect of the improvement of quality is to suppress the magnitude of the influence coming from subtle changes of noise factors. To model and control process variability induced by noise factors we take a response surface approach. The derivative of the standard response function with respect to noise factors, i. e., the slopes of the response function in the direction of the noise factors, play an important role in the study of the minimum process variance. For better understanding of the process variability, we study various properties of both biased and the unbiased estimators of the process variance. Response surface modeling techniques and the ideas involved with variance modeling and estimation through the function of the aforementioned derivatives is a valuable concept in this study. In what follows, we describe the use of the response surface methodology for situations in which noise factors are used. The approach is to combine Taguchi's notion of heterogeneous variability with standard design and modeling techniques available in response surface methodology.<br>Ph. D.
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Cheng, Aili. "CONFIDENCE REGIONS FOR OPTIMAL CONTROLLABLE VARIABLES FOR THE ROBUST PARAMETER DESIGN PROBLEM." Diss., Temple University Libraries, 2012. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214761.
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Statistics<br>Ph.D.<br>In robust parameter design it is often possible to set the levels of the controllable factors to produce a zero gradient for the transmission of variability from the noise variables. If the number of control variables is greater than the number of noise variables, a continuum of zero-gradient solutions exists. This situation is useful as it provides the experimenter with multiple conditions under which to configure a zero gradient for noise variable transmission. However, this situation requires a confidence region for the multiple-solution factor levels that provides proper simultaneous coverage. This requirement has not been previously recognized in the literature. In the case where the number of control variables is greater than the number of noise variables, we show how to construct critical values needed to maintain the simultaneous coverage rate. Two examples are provided as a demonstration of the practical need to adjust the critical values for simultaneous coverage. The zero-gradient confidence region only focuses on the variance, and there are in fact many such situations in which focus is or could be placed entirely on the process variance. In the situation where both mean and variance need to be considered, a general confidence region in control variables is developed by minimizing weighted mean square error. This general method is applicable to many situations including mixture experiments which have an inherit constraint on the control factors. It also gives the user the flexibility to put different weights on the mean and variance parts for simultaneous optimization. It turns out that the same computational algorithm can be used to compute the dual confidence region in both control factors and the response variable.<br>Temple University--Theses
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Sar, Preeti. "Eco-Inspired Robust Control Design Algorithm For Linear Systems with Real Parameter Uncertainty." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1367439491.
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Blanchard, Emmanuel. "Polynomial Chaos Approaches to Parameter Estimation and Control Design for Mechanical Systems with Uncertain Parameters." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/26727.
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Mechanical systems operate under parametric and external excitation uncertainties. The polynomial chaos approach has been shown to be more efficient than Monte Carlo approaches for quantifying the effects of such uncertainties on the system response. This work uses the polynomial chaos framework to develop new methodologies for the simulation, parameter estimation, and control of mechanical systems with uncertainty.
This study has led to new computational approaches for parameter estimation in nonlinear mechanical systems. The first approach is a polynomial-chaos based Bayesian approach in which maximum likelihood estimates are obtained by minimizing a cost function derived from the Bayesian theorem. The second approach is based on the Extended Kalman Filter (EKF). The error covariances needed for the EKF approach are computed from polynomial chaos expansions, and the EKF is used to update the polynomial chaos representation of the uncertain states and the uncertain parameters. The advantages and drawbacks of each method have been investigated.
This study has demonstrated the effectiveness of the polynomial chaos approach for control systems analysis. For control system design the study has focused on the LQR problem when dealing with parametric uncertainties. The LQR problem was written as an optimality problem using Lagrange multipliers in an extended form associated with the polynomial chaos framework. The solution to the Hâ problem as well as the H2 problem can be seen as extensions of the LQR problem. This method might therefore have the potential of being a first step towards the development of computationally efficient numerical methods for Hâ design with parametric uncertainties.
I would like to gratefully acknowledge the support provided for this work under NASA Grant NNL05AA18A.<br>Ph. D.
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Moeeni, Farhad. "A parameter design framework for designing robust Just-In-Time production systems with Kanban." Diss., The University of Arizona, 1992. http://hdl.handle.net/10150/186073.
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Many industries are in the process of adopting or considering adoption of the Just-In-Time philosophy and techniques. Most of these firms are not characterized by the type of environment which is required for transferring the philosophy, such as stable manufacturing factors. The adverse effect of environmental uncertainties on the operating phase of Just-In-Time systems in general and the performance of Kanban systems in particular has been well documented. This dissertation proposes a framework for designing robust Kanban systems, by adopting the product and process design approach pioneered by Genichi Taguchi. A robust Kanban systems is one whose performance is insensitive to environmental uncertainties. As part of our investigation, we illustrate how frequency domain experiments can be used in order to investigate the effect of noise factors and their interactions on the performance of a Kanban system. The technique allows us to examine simultaneously many factors that previous researchers have studied separately, and so explore and identify important interaction effects. We develop a general framework for designing a robust Kanban system that can be applied to different production configurations, and illustrate the robust design process via a simulation study of a three-stage manufacturing line.
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Chandavarkar, Rohan Vivek. "Eco-inspired Robust Control Design for Linear Time-Invariant systems with Real Parameter Uncertainty." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1373467190.
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Yenidunya, Baris. "Robust Design With Binary Response Using Mahalanobis Taguci System." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610736/index.pdf.
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In industrial quality improvement and design studies, an important aim is to improve the product or process quality by determining factor levels that would result in satisfactory quality results. In these studies, quality characteristics that are qualitative are often encountered. Although there are many effective methods proposed for parameter optimization (robust design) with continuous responses, the methods available for qualitative responses are limited. In this study, a parameter optimization method for solving binary response robust design problems is proposed. The proposed method uses Mahalanobis Taguchi System to form a classification model that provides a distance function to separate the two response classes. Then, it finds the product/process variable settings that minimize the distance from the desired response class using quadratic programming.
The proposed method is applied on two cases previously studied using Logistic Regression. The classification models are formed and the parameter optimization is conducted using the formed MTS models. The results are compared with those of the Logistic Regression. Conclusions and suggestions for future work are given.
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Wiedemann, Michael. "Robust parameter design for agent-based simulation models with application in a cultural geography model." Thesis, Monterey, California : Naval Postgraduate School, 2010. http://edocs.nps.edu/npspubs/scholarly/theses/2010/Jun/10Jun%5FWiedemann.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2010.<br>Thesis Advisor(s): Johnson, Rachel T. ; Second Reader: Baez, Francisco R, "June 2010." Description based on title screen as viewed on July 15, 2010. Author(s) subject terms: Cultural Geography, Agent-Based Model (ABM), Irregular Warfare (IW), Theory of planned Behavior (TpB), Baysian Belief Nets (BBN), Counterinsurgency Operations (COIN), Stability Operations, Discrete Event Simulation (DES), Design of Experiments (DOX), Robust Parameter Design (RPD). Includes bibliographical references (p. 69-70). Also available in print.
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Proddaturi, Amarnath. "Robust parameter design and finite element analysis for a non-pneumatic tire with low vibration." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1263408710/.
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Erdural, Serkan. "A Method For Robust Design Of Products Or Processes With Categorical Response." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/3/12608015/index.pdf.
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In industrial processes decreasing variation is very important while achieving the targets. For manufacturers, finding out optimal settings of product and process parameters that are capable of producing desired results under great conditions is crucial. In most cases, the quality response is measured on a continuous scale. However, in some cases, the desired quality response may be qualitative (categorical). There are many effective methods to design robust products/process through industrial experimentation when the response variable is continuous. But methods proposed so far in the literature for robust design with categorical response variables have various limitations.
This study offers a simple and effective method for the analysis of categorical response data for robust product or process design. This method handles both location and dispersion effects to explore robust settings in an effective way. The method is illustrated on two cases: A foam molding process design and an iron-casting process design.
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Pickle, Stephanie M. "Semiparametric Techniques for Response Surface Methodology." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/28517.
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Many industrial statisticians employ the techniques of Response Surface Methodology (RSM) to study and optimize products and processes. A second-order Taylor series approximation is commonly utilized to model the data; however, parametric models are not always adequate. In these situations, any degree of model misspecification may result in serious bias of the estimated response. Nonparametric methods have been suggested as an alternative as they can capture structure in the data that a misspecified parametric model cannot. Yet nonparametric fits may be highly variable especially in small sample settings which are common in RSM. Therefore, semiparametric regression techniques are proposed for use in the RSM setting. These methods will be applied to an elementary RSM problem as well as the robust parameter design problem.<br>Ph. D.
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Adiga, Nagesh. "Contributions to variable selection for mean modeling and variance modeling in computer experiments." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43592.
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This thesis consists of two parts. The first part reviews a Variable Search, a variable selection procedure for mean modeling. The second part deals with variance modeling for robust parameter design in computer experiments.
In the first chapter of my thesis, Variable Search (VS) technique developed by Shainin (1988) is reviewed. VS has received quite a bit of attention from experimenters in industry. It uses the experimenters' knowledge about the process, in terms of good and bad settings and their importance. In this technique, a few experiments are conducted first at the best and worst settings of the variables to ascertain that they are indeed different from each other. Experiments are then conducted sequentially in two stages, namely swapping and capping, to determine the significance of variables, one at a time. Finally after all the significant variables have been identified, the model is fit and the best settings are determined.
The VS technique has not been analyzed thoroughly. In this report, we analyze each stage of the method mathematically. Each stage is formulated as a hypothesis test, and its performance expressed in terms of the model parameters. The performance of the VS technique is expressed as a function of the performances in each stage. Based on this, it is possible to compare its performance with the traditional techniques.
The second and third chapters of my thesis deal with variance modeling for robust parameter design in computer experiments. Computer experiments based on engineering models might be used to explore process behavior if physical experiments (e.g. fabrication of nanoparticles) are costly or time consuming. Robust parameter design (RPD) is a key technique to improve process repeatability. Absence of replicates in computer experiments (e.g. Space Filling Design (SFD)) is a challenge in locating RPD solution. Recently, there have been studies (e.g. Bates et al. (2005), Chen et al. (2006), Dellino et al. (2010 and 2011), Giovagnoli and Romano (2008)) of RPD issues on computer experiments. Transmitted variance model (TVM) proposed by Shoemaker and Tsui. (1993) for physical experiments can be applied in computer simulations. The approaches stated above rely heavily on the estimated mean model because they obtain expressions for variance directly from mean models or by using them for generating replicates. Variance modeling based on some kind of replicates relies on the estimated mean model to a lesser extent. To the best of our knowledge, there is no rigorous research on variance modeling needed for RPD in computer experiments.
We develop procedures for identifying variance models. First, we explore procedures to decide groups of pseudo replicates for variance modeling. A formal variance change-point procedure is developed to rigorously determine the replicate groups. Next, variance model is identified and estimated through a three-step variable selection procedure. Properties of the proposed method are investigated under various conditions through analytical and empirical studies. In particular, impact of correlated response on the performance is discussed.
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Olabode, John A. "Analysis of the performance of an optimization model for time-shiftable electrical load scheduling under uncertainty." Thesis, Monterey, California: Naval Postgraduate School, 2016. http://hdl.handle.net/10945/51591.
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Approved for public release; distribution is unlimited<br>To ensure sufficient capacity to handle unexpected demands for electric power, decision makers often over-estimate expeditionary power requirements. Therefore, we often use limited resources inefficiently by purchasing more generators and investing in more renewable energy sources than needed to run power systems on the battlefield. Improvement of the efficiency of expeditionary power units requires better managing of load requirements on the power grids and, where possible, shifting those loads to a more economical time of day. We analyze the performance of a previously developed optimization model for scheduling time-shiftable electrical loads in an expeditionary power grids model in two experiments. One experiment uses model data similar to the original baseline data, in which expected demand and expected renewable production remain constant throughout the day. The second experiment introduces unscheduled demand and realistic fluctuations in the power production and the demand distributions data that more closely reflect actual data. Our major findings show energy grid power production composition affects which uncertain factor(s) influence fuel con-sumption, and uncertainty in the energy grid system does not always increase fuel consumption by a large amount. We also discover that the generators running the most do not always have the best load factor on the grid, even when optimally scheduled.<br>Lieutenant Commander, United States Navy
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Johann, Matthew A. "Fire-Robust Structural Engineering: A Framework Approach to Structural Design for Fire Conditions." Link to electronic thesis, 2002. http://www.wpi.edu/Pubs/ETD/Available/etd-1219102-155849.
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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: structural engineering; fire safety; framework approach; performance-based design; information management; finite element; lumped-parameter; laboratory tests; steel; beam; restrained; plastic analysis. Includes bibliographical references (p. 180-182).
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Pozueta, Fernández Maria Lourdes. "Errores en la búsqueda de condiciones robustas. Metodologías para evitarlos." Doctoral thesis, Universitat Politècnica de Catalunya, 2001. http://hdl.handle.net/10803/5833.
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El problema de encontrar condiciones robustas al efecto de factores no controlados es un tema que interesa enormemente a las empresas ya que es una característica que demanda el mercado. Existen básicamente dos métodos para estudiar el problema: El que se basa en el método propuesto por G. Taguchi a comienzos de los 80's con el que se aproxima la variabilidad a partir de matrices producto y se seleccionan las condiciones robustas minimizando la respuesta, o el que parte de una matriz más económica que permite estimar un modelo para la respuesta Y en función de los factores de control y ruido, y estudia las condiciones robustas a partir de las interacciones entre los factores ruido y los factores de control. Aunque en un principio cabrían esperar resultados muy similares analizando un mismo problema por las dos vías hemos encontrado ejemplos donde las conclusiones son muy dispares y por ello nos hemos planteado este trabajo de investigación para encontrar las causas de estas diferencias.<br/>El trabajo de investigación lo hemos iniciado estudiando la naturaleza de las superficies asociadas a la variabilidad provocada por factores ruido realizando el estudio de forma secuencial aumentando el número de factores ruido. Hemos demostrado que independientemente de que la métrica seleccionada sea s2(Y), s(Y) o lo(s(Y)) las superficies difícilmente podrán ser aproximadas por polinomios de primer orden en los factores de control llegando a la conclusión de que algunas de las estrategias habituales que los experimentadores utilizan en la práctica difícilmente llevan a un buen conocimiento de esta superficie. Por ejemplo no es adecuado colocar un diseño 2k-p de Resolución III en los factores de control en una matriz producto siendo recomendables diseños de Resolución IV con puntos centrales.<br/>A continuación se han supuesto dos fuentes de variación en la respuesta debidas a ruido, fuentes desconocidas para el experimentador, y se ha estudiado la sensibilidad de los dos métodos para recoger estas oportunidades de reducción de la variabilidad demostrándose que el modelo para métricas resumen está más preparado para recoger todas las fuentes de variación que el modelo a partir de métricas no-resumen, el cual es muy sensible a la estimación del modelo de Y.<br/>Por último se ha investigado sobre los errores más comunes a la hora de seleccionar las condiciones robustas a partir de gráficos.
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Beteto, Marco Antonio Leite. "Less conservative conditions for the robust and Gain-Scheduled LQR-state derivative controllers design /." Ilha Solteira, 2019. http://hdl.handle.net/11449/180976.
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Orientador: Edvaldo Assunção<br>Resumo: Neste trabalho é proposta a resolução do problema do regulador linear quadrático (Linear Quadratic Regulator - LQR) via desigualdades matriciais lineares (Linear Matrix Inequalities - LMIs) para sistemas lineares e invariantes no tempo sujeitos a incertezas politópicas, bem como para sistemas lineares sujeitos a parâmetros variantes no tempo (Linear Parameter Varying - LPV). O projeto dos controladores é baseado na realimentação derivativa. A escolha da realimentação derivativa se dá devido à sua fácil implementação em certas aplicações como, por exemplo, no controle de vibrações. Os sinais usados na realimentação são aceleração e velocidade, sendo obtidos por meio de acelerômetros. Por meio do método proposto é possível obter condições LMIs para a síntese de controladores que garantam a estabilização do sistema em malha fechada, sendo que os controladores possuem desempenho otimizado. Para a formulação das condições LMIs, uma função de Lyapunov do tipo quadrática é utilizada. Exemplos teóricos e simulações são utilizados como forma de validação dos métodos propostos, além de mostrar que os novos resultados apresentam condições menos conservadoras. Além disso, ao final é apresentada uma implementação prática em um sistema de suspensão ativa, produzida pela Quanser®.<br>Abstract: The resolution of linear quadratic regulator (LQR) problem via linear matrix inequalities (LMIs) for linear time-invariant systems subject to polytopic uncertainties, as linear systems subjects to linear parameter varying (LPV), is proposed in this work. The controllers' designs are based on the state derivative feedback. The aim to the choice of the state derivative feedback is your easy implementation in a class of mechanical systems, such as in vibration control, for example. The signals used for feedback are acceleration and velocity, it is obtained by means of accelerometers. Through the proposed method it is possible to obtain LMIs conditions for the synthesis of controllers that guarantee the stabilisation of the closed-loop system, being that the controllers have optimised performance. For the LMIs conditions formulations, a Lyapunov function of type quadratic is used. As a form of validation, theoretical examples and simulations are performed, besides to show that the new results are less conservative. Furthermore, a practical implementation in an active suspension system, produced by Quanser®, is performed.<br>Mestre
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Ittiwattana, Waraporn. "A Method for Simulation Optimization with Applications in Robust Process Design and Locating Supply Chain Operations." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1030366020.
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KHALAF, POYA. "Design, Control, and Optimization of Robots with Advanced Energy Regenerative Drive Systems." Cleveland State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=csu1552923998768344.
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Huang, Hsun-Hsuan. "Controller Design for Stability and Rollover Prevention of Multi-body Ground Vehicles with Uncertain Dynamics and Faults." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1253631414.
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An, Na. "Resource Modeling and Allocation in Competitive Systems." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6997.
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This thesis includes three self-contained projects:
In the first project Bidding strategies and their impact on the auctioneer's revenue in combinatorial auctions, focusing on combinatorial auctions, we propose a simple and efficient model for evaluating the value of any bundle given limited information, design bidding strategies that efficiently select desirable bundles, and evaluate the performance of different bundling strategies under various market settings.
In the second project Retailer shelf-space management with promotion effects, promotional investment effects are integrated with retail store assortment decisions and shelf space allocation. An optimization model for the category shelf-space allocation incorporating promotion effects is presented. Based on the proposed model, a category shelf space allocation framework with trade allowances is presented where a multi-player Retailer Stackelberg game is introduced to model the interactions between retailer and manufacturers.
In the third project Supply-chain oriented robust parameter design, we introduce the game theoretical method, commonly used in supply-chain analysis to solve potential conflicts between manufacturers at various stages. These manufacturing chain partners collaboratively decide parameter design settings of the controllable factors to make the product less sensitive to process variations.
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Qian, Gengjian. "Analyse de sensibilité et robustesse dans le génie industriel : méthodologies et applications aux essais de chocs." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1064/document.
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Plus d'un million de personnes meurent dans des accidents sur les routes du monde et beaucoup de millions sont gravement blessés chaque année. Selon les études, ‘Run-Off-Road accidents (ROR)’, c'est-à-dire que le véhicule a au moins une collision avec des équipements routiers, représentent environ 10% des accidents routières, mais 45% de tous les accidents mortels sont des ROR. Les dispositifs de retenue des véhicules (DDR) sont les infrastructures installées sur la route pour fournir un niveau de confinement du véhicule ‘hors de contrôle’. La barrière de sécurité routière est un DDR continu installé à côté ou sur la réserve centrale d'une route pour empêcher les véhicules errants de s'écraser sur les obstacles routiers et de les conserver en toute sécurité. Les résultats statistique montrent que l'existence des barrières peut réduire les morts jusqu'à un facteur de 4 par rapport aux collisions contre d'autres obstacles routiers. Les performances de sauvetage d'un DDR dépendent de la conception de l'appareil. Des normes telles que EN1317 ont normalisé les conditions des essais de chocs sous lesquelles une conception de DDR doit être testée et ont défini les critères pour l'évaluation des performances d'une conception. En fait, un DDR ne puisse pas vraiment être optimisé: il existe des critères multiples pour l'évaluation de la performance d'un DDR et tous les critères ne peuvent pas être optimisés en même temps; les conditions de travail d’un DDR, c'est-à-dire les conditions d'impact d’un DDR avec un véhicule errant, sont nombreuses; les facteurs incertains du DDR peuvent dégrader les performances d'une conception. La thèse vise à définir une approche qui peut servir : l'analyse de sensibilité (AS) et la conception robuste du DDR ; enrichissement des normes existantes dans la conception du DDR. Le cas d'une barrière de sécurité routière est spécifié dans l'étude : une barrière a été testée expérimentalement, le programme Ls-Dyna est utilisé pour la simulation de choc de l'appareil ; en tenant compte des propriétés du modèle de choc, les efficacités de différentes méthodes de l’AS ont été étudiées ; les influences des facteurs critiques dont les incertitudes contribuent le plus à l'instabilité de la barrière ont été quantifiées avec les approches d’AS sélectionnées ; compte tenu des incertitudes des facteurs critiques, l’optimisation robuste de multi-objectif de la barrière est réalisée ; des simulations d'impact de la barrière optimisée ont été effectuées sous des conditions d'impact différentes pour évaluer ses performances dans les véritables accidents. Les approches présentées dans l'article peuvent être utiles pour la conception d'autres DDR ou plus largement d'autres systèmes d'ingénierie complexes. On peut espérer que l'analyse de robustesse et l'analyse de la généralisation (c'est-à-dire l'évaluation de la performance du DDR sous différentes conditions d'impact) du DDR pourraient enrichir les normes de la conception des DDR<br>More than 1 million people die in crashes on the world’s roads and many millions are seriously injured each year. According to the studies: Run-Off-Road accidents (ROR), i.e. the vehicle run-off the road into the roadside and has at least one collision with either roadside equipment or the roadside itself, “represent about 10% of the total road accidents, while 45% of all fatal accidents are ROR”. Vehicle Restraint Systems (VRS) are the infrastructures installed on the road to provide a level of containment for an errant vehicle. Safety barrier is “continuous VRS installed alongside, or on the central reserve, of a road to prevent errant vehicles from crashing on roadside obstacles, and to retain them safely”. Statistic results show that “the existence of protective barriers on road can reduce fatalities up to a factor of 4 when compared to collisions against other road obstacles.” The life-saving performances of a VRS depend on the design of the device. Standards such as EN1317 normalized the impact conditions under which a design of VRS must be tested by crash tests, and defined the criteria for performance evaluation of a design. While a VRS cannot really be optimized: Multi-criteria exist for performance evaluation of a VRS and all the criteria cannot be optimized in the same time; the impact conditions of the VRS with the errant vehicle are numerous; uncertain factors of the VRS may degrade the performances of a design. The thesis aims to define an approach that can serve: sensitivity analysis (SA) and robust design of the VRS; Enrichment for the existing standards in the design of VRS. The case of a safety barrier is specified in the study: a safety barrier has been test experimentally, the program Ls-Dyna was used for crash simulation of the device; considering properties of the crash model, efficiencies of different SA methods were studied and influences of the critical factors whose uncertainties contribute the most to the instability of the barrier were quantified with the selected SA approaches; considering the uncertainties of the critical factors, Multi-Objective robust optimization of the tested barrier were realized; under different impact conditions, crash simulations of the optimized barrier were carried out to evaluate its performances in the real crash accidents. The approaches presented in the article can be useful for the design of other VRS or more broadly, other complex engineering systems. Hopefully, the robustness analysis and generalization analysis (i.e. performance evaluation of the VRS under different impact conditions) of the safety barrier could enrich the standards for the design of VRS
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Tan, Matthias H. Y. "Contributions to quality improvement methodologies and computer experiments." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/48936.
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This dissertation presents novel methodologies for five problem areas in modern quality improvement and computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate quality control, model selection for split plot experiments, and construction of minimax designs.
Selective assembly has traditionally been used to achieve tight specifications on the clearance of two mating parts. Chapter 1 proposes generalizations of the selective assembly method to assemblies with any number of components and any assembly response function, called generalized selective assembly (GSA). Two variants of GSA are considered: direct selective assembly (DSA) and fixed bin selective assembly (FBSA). In DSA and FBSA, the problem of matching a batch of N components of each type to give N assemblies that minimize quality cost is formulated as axial multi-index assignment and transportation problems respectively. Realistic examples are given to show that GSA can significantly improve the quality of assemblies.
Chapter 2 proposes methods for robust design optimization with time consuming computer simulations. Gaussian process models are widely employed for modeling responses as a function of control and noise factors in computer experiments. In these experiments, robust design optimization is often based on average quadratic loss computed as if the posterior mean were the true response function, which can give misleading results. We propose optimization criteria derived by taking expectation of the average quadratic loss with respect to the posterior predictive process, and methods based on the Lugannani-Rice saddlepoint approximation for constructing accurate credible intervals for the average loss. These quantities allow response surface uncertainty to be taken into account in the optimization process.
Chapter 3 proposes a Bayesian method for identifying mean shifts in multivariate normally distributed quality characteristics. Multivariate quality characteristics are often monitored using a few summary statistics. However, to determine the causes of an out-of-control signal, information about which means shifted and the directions of the shifts is often needed. We propose a Bayesian approach that gives this information. For each mean, an indicator variable that indicates whether the mean shifted upwards, shifted downwards, or remained unchanged is introduced. Default prior distributions are proposed. Mean shift identification is based on the modes of the posterior distributions of the indicators, which are determined via Gibbs sampling.
Chapter 4 proposes a Bayesian method for model selection in fractionated split plot experiments. We employ a Bayesian hierarchical model that takes into account the split plot error structure. Expressions for computing the posterior model probability and other important posterior quantities that require evaluation of at most two uni-dimensional integrals are derived. A novel algorithm called combined global and local search is proposed to find models with high posterior probabilities and to estimate posterior model probabilities. The proposed method is illustrated with the analysis of three real robust design experiments. Simulation studies demonstrate that the method has good performance.
The problem of choosing a design that is representative of a finite candidate set is an important problem in computer experiments. The minimax criterion measures the degree of representativeness because it is the maximum distance of a candidate point to the design. Chapter 5 proposes algorithms for finding minimax designs for finite design regions. We establish the relationship between minimax designs and the classical set covering location problem in operations research, which is a binary linear program. We prove that the set of minimax distances is the set of discontinuities of the function that maps the covering radius to the optimal objective function value, and optimal solutions at the discontinuities are minimax designs. These results are employed to design efficient procedures for finding globally optimal minimax and near-minimax designs.
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Grandicki, Andreas, and Mattias Lokgård. "Parametric CAD Modeling to aid Simulation-Driven Design : An evaluation and improvement of methods used at Scania." Thesis, Linköpings universitet, Maskinkonstruktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138121.
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This report documents a thesis conducted at Scania CV AB in Södertälje, Sweden. The main purpose of the thesis has been to examine and improve upon current practices of parametric CAD-modeling at Scania, with the ultimate goal of increased design automation and simulation-driven design. The thesis was initiated with a literature study, mainly covering the fields of parametric CAD-modeling, design automation and knowledge-based engineering. Furthermore, a questionnaire and multiple interviews were conducted to assess the awareness and mind-set of the employees. Finally, a case-study was carried out to follow current methodologies, and address any deficiencies found. Some of the most important findings were that while parametric modeling has considerable potential in enabling design automation, it is crucial, and most beneficial in terms of automation efficiency, to start with the fundamentals, namely achieving a uniform modeling practice. With these findings, a new proposed methodology has been introduced, as well as a recommended plan for a widespread implementation of parametric modeling at Scania. Such implementation would allow for shorter lead-times, faster adaptation to changing conditions, and reduced development expenditures.
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Sun, Jin. "Conquering Variability for Robust and Low Power Designs." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145458.
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As device feature sizes shrink to nano-scale, continuous technology scaling has led to a large increase in parameter variability during semiconductor manufacturing process. According to the source of uncertainty, parameter variations can be classified into three categories: process variations, environmental variations, and temporal variations. All these variation sources exert significant influences on circuit performance, and make it more challenging to characterize parameter variability and achieve robust, low-power designs. The scope of this dissertation is conquering parameter variability and successfully designing efficient yet robust integrated circuit (IC) systems. Previous experiences have indicated that we need to tackle this issue at every design stage of IC chips. In this dissertation, we propose several robust techniques for accurate variability characterization and efficient performance prediction under parameter variations. At pre-silicon verification stage, a robust yield prediction scheme under limited descriptions of parameter uncertainties, a robust circuit performance prediction methodology based on importance of uncertainties, and a robust gate sizing framework by ElasticR estimation model, have been developed. These techniques provide possible solutions to achieve both prediction accuracy and computation efficiency in early design stage. At on-line validation stage, a dynamic workload balancing framework and an on-line self-tuning design methodology have been proposed for application-specific multi-core systems under variability-induced aging effects. These on-line validation techniques are beneficial to alleviate device performance degradation due to parameter variations and extend device lifetime.
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Can, Fatih Cemal. "Inertial Parameter Design Of Spatial Mechanisms." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1254895/index.pdf.
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In this thesis, the inertial parameters of a spatial mechanism are used in order to optimize various aspects of the dynamic behaviour of the mechanism (such as minimizing actuator torque/ force fluctuations, shaking force/moment balancing, etc.) while the effects of loads are considered as well. Here, inertial parameters refer to the mass, 6 elements of the inertia tensor and coordinates of the center of mass of the links.
The concept of Force Fluctuation Number (FFN) is utilized to optimize the dynamic behaviour of the mechanism. By using the FFN concept, one obtains a number of linear equations to be satisfied by the optimal inertial parameters. In general, the number of such equations is less than the number of the inertial parameters. Therefore, some of the inertial parameters may be selected freely in order to satisfy other design constraints.
Using MATHEMATICA, a program has been developed to obtain the linear equations to be satisfied by the optimal inertial parameters. The developed program includes a kinematic and force analysis module, which
can be used independently for a complete kinematic and dynamic analysis of any one degree of freedom, single loop, spatial mechanism. The different closures of the mechanism may be identified by using the developed package and these analyses can be performed on any selected closure of the mechanism.
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Konstantinou, Maria. "Locally optimal and robust designs for two-parameter nonlinear models with application to survival models." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/361328/.
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Kircheis, Robert [Verfasser], and Stefan [Akademischer Betreuer] Körkel. "Structure Exploiting Parameter Estimation and Optimum Experimental Design Methods and Applications in Microbial Enhanced Oil Recovery / Robert Kircheis ; Betreuer: Stefan Körkel." Heidelberg : Universitätsbibliothek Heidelberg, 2015. http://d-nb.info/118039657X/34.
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Kircheis, Robert [Verfasser], and Stefan [Akademischer Betreuer] Körkel. "Structure Exploiting Parameter Estimation and Optimum Experimental Design Methods and Applications in Microbial Enhanced Oil Recovery / Robert Kircheis ; Betreuer: Stefan Körkel." Heidelberg : Universitätsbibliothek Heidelberg, 2016. http://d-nb.info/1180736540/34.
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Wu, Yier. "Optimal pose selection for the identification of geometric and elastostatic parameters of machining robots." Phd thesis, Ecole des Mines de Nantes, 2014. http://tel.archives-ouvertes.fr/tel-00983277.
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The thesis deals with the optimal pose selection for geometric and elastostatic calibration for industrial robots employed in machining of large parts. Particular attention is paid to the improvement of robot positioning accuracy after compensation of the geometric and elastostatic errors. To meet the industrial requirements of machining operations, a new approach for calibration experiments design for serial and quasi-serial industrial robots is proposed. This approach is based on a new industry-oriented performance measure that evaluates the quality of calibration experiment plan via the manipulator positioning accuracy after error compensation, and takes into account the particularities of prescribed manufacturing task by introducing manipulator test-poses. Contrary to previous works, the developed approach employs an enhanced partial pose measurement method, which uses only direct position measurements from an external device and allows us to avoid the non-homogeneity of relevant identification equations. In order to consider the impact of gravity compensator that creates closed-loop chains, the conventional stiffness model is extended by including in it some configuration dependent elastostatic parameters, which are assumed to be constant for strictly serial robots. Corresponding methodology for calibration of the gravity compensator models is also proposed. The advantages of the developed calibration techniques are validated via experimental study, which deals with geometric and elastostatic calibration of a KUKA KR-270 industrial robot.
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Eufrázio, Sofia Raquel Lavado. "Avaliação do efeito barreira das estradas na abundância e uso do espaço do rato-do-campo (Apodemus sylvaticus)." Master's thesis, Universidade de Évora, 2010. http://hdl.handle.net/10174/20841.
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As estradas são essenciais ao desenvolvimento da economia, mas também um dos maiores problemas de conservação. Porém, os seus efeitos nas populações de micromamíferos são controversos. Este estudo pretendeu quantificar o efeito da estrada nos parâmetros populacionais e no padrão espacial do rato-do-campo (Apodemus sylvaticus) incluindo os efeitos do microhabitat. Uma área de montado atravessada por uma estrada e outra sem o efeito de estrada (controlo) foram comparadas no sul de Portugal. Os parâmetros populacionais avaliaram-se pelo modelo robusto de Pollock. O efeito do microhabitat no uso do espaço verificou-se através de modelos lineares mistos generalizados (GLMM). Os resultados sugerem que a presença da estrada afecta negativamente os parâmetros populacionais do rato-do-campo. Contudo, na presença da estrada, as bermas parecem ser mais benéficas para esta espécie do que as áreas sem efeito de estrada. Os resultados revelam também a importância de diferentes características de microhabitat para cada população de Apodemus sylvaticus. – ABSTRACT: Roads are essential for economic development but they are also a global concern in wildlife conservation. Nevertheless, there is a controversy about the effects of roads on small mammals. The main goal of this study was to quantify the effect of the road in the population parameters and in the spatial pattern of the wood mouse (Apodemus sylvaticus) including microhabitat effects. We compared populations of two areas: one crossed by a national road and other without the effect of a road in southern Portugal. We used Pollock's robust design to evaluate population parameters. Generalized linear mixed models were used to analyse the microhabitat effect. Our results suggest that the presence of the road negatively affects population parameters of wood mouse. However, in the presence of the road, road verges seem to be more suitable for the species than roadless areas. Our results also revealed the importance of different microhabitat characteristics, for each population of wood mouse.
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Kalas, Vinayak Jagannathrao. "Application-oriented optimization of robot elastostatic calibration : implementation on hexapod positioning systems." Thesis, Montpellier, 2020. http://www.theses.fr/2020MONTS018.
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Les hexapodes sont de plus en plus utilisés pour des applications de positionnement de haute précision à 6 degrés de liberté, comme pour le positionnement des miroirs des télescopes ou pour le positionnement des échantillons dans les synchrotrons. Ces robots sont conçus et commandés pour faire preuve de grande répétabilité et de grande justesse. Cependant, la souplesse structurelle de ces systèmes de positionnement limite leur précision de positionnement. Comme les exigences de précision deviennent de plus en plus strictes dans les applications émergentes, il devient nécessaire de compenser ces déformations.À cet égard, tout d'abord, une méthode d'étalonnage élastostatique des hexapodes est présentée. Cette méthode utilise un modèle de paramètre de rigidité forfaitaire pour paramétrer la relation entre les flèches de la plate-forme et la force / le moment qui lui est appliqué. Ces paramètres peuvent être estimés à l'aide de mesures de déflexion effectuées en utilisant des forces / moments connus appliqués sur la plate-forme. Les paramètres estimés peuvent ensuite être utilisés pour prévoir et corriger les erreurs de positionnement des hexapodes dues à la conformité.Deuxièmement, une nouvelle approche est présentée pour optimiser le processus d’identification des paramètres de raideur de l’étalonnage élastostatique. Cette approche repose sur l’utilisation de critères qui permettent de déterminer le meilleur ensemble de poses et de forces pour identifier les paramètres de raideur. Les paramètres identifiés dans les conditions expérimentales (poses et forces) suggérées par ces critères permettent une contribution minimum des erreurs influençant l’identification des raideurs (incertitude des mesures des déflections et erreurs des forces appliquées) sur la qualité de la compensation. De plus, suivre cette approche maximise également la précision après compensation aux poses souhaitées, le long des axes souhaités, et avec les combinaisons force/moment souhaitées sur la plateforme. Ce cadre d’optimisation pour l’identification des raideurs assure la meilleure compensation des erreurs de positionnement dues à la souplesse structurelle, selon les exigences de positionnement de l’application en question.Enfin, une méthode est présentée qui permet de s’affranchir des effets dues à la thermique sur la mesure des 6 degrés de liberté de la pose de la plateforme d’un hexapode. Cette méthode est nécessaire lorsque les déflections dues à la thermique de l’hexapode sont suffisamment importantes pour avoir un impact sur les résultats d’une étude, ce qui était le cas avec certains des tests effectués pour valider les méthodes développées dans cette thèse.L’efficacité des méthodes présentées a été validée au moyen d’études en simulation sur un bipède, et d’études expérimentales sur un système de positionnement hexapode de haute précision<br>Hexapods are increasingly being used for high-precision 6-DOF positioning applications such as for positioning mirrors in telescopes and for positioning samples in synchrotrons. These robots are designed and controlled to be very repeatable and accurate. However, structural compliance of these positioning systems limits their positioning accuracy. As accuracy requirements become more stringent in emerging applications, compensating for inaccuracy due to structural compliance becomes necessary.In this regard, firstly, a method for elastostatic calibration of hexapods is presented. This method uses a lumped stiffness parameter model to parametrize the relationship between the platform deflections and the force/moment applied on it. These parameters can be estimated using deflection measurements performed using known forces/moments applied on the platform. The estimated parameters can then be used to predict and correct hexapod’s positioning errors due to compliance.Secondly, a new approach is presented to optimize stiffness identification for robot elastostatic calibration. In this, a framework is proposed to formulate criteria to choose best set of poses and forces for stiffness identification experiment. The parameters identified under experimental conditions (poses and forces) suggested by these criteria ensure minimum impact of errors influencing stiffness identification (uncertainty of deflection measurements and errors in forces applied) on compensation quality. Additionally, it also maximizes accuracy after compensation at desired pose(s), along desired axe(s) of the platform and with desired forces/moments on the platform. This stiffness identification optimization framework ensures best compensation for positioning errors due to compliance as per the positioning requirements of the application at hand.Lastly, a method is presented to eliminate the influence of thermal deflection of a hexapod on the measured 6-DOF pose of its platform. This method is necessary when thermal deflections of the hexapod are large enough to impact results of a study, which was the case with some tests performed to validate methods developed in this thesis.The efficacy of presented methods have been validated by means of simulation studies on a bipod and experimental studies on a high-precision hexapod positioning system
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Riechel, Andrew T. "Force-Feasible Workspace Analysis and Motor Mount Disturbance Compensation for Point-Mass Cable Robots." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5243.
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Cable-actuated manipulators (or 'cable robots') constitute a relatively new classification of robots which use motors, located at fixed remote locations, to manipulate an end-effector by extending or retracting cables. These manipulators possess a number of unique properties which make them proficient with tasks involving high payloads, large workspaces, and dangerous or contaminated environments. However, a number of challenges exist which have limited the mainstream emergence of cable robots. This thesis addresses two of the most important of these issues-- workspace analysis and disturbance compensation.
Workspace issues are particularly important, as many large-scale applications require the end-effector to operate in regions of a particular shape, and to exert certain minimum forces throughout those regions. The 'Force-Feasible Workspace' represents the set of end-effector positions, for a given robot design, for which the robot can exert a set of required forces on its environment. This can be considered as the robot's 'usable' workspace, and an analysis of this workspace shape for point-mass cable robots is therefore presented to facilitate optimal cable robot design. Numerical simulation results are also presented to validate the analytical results, and to aid visualization of certain complex workspace shapes.
Some cable robot applications may require mounting motors to moving bases (i.e. mobile robots) or other surfaces which are subject to disturbances (i.e. helicopters or crane arms). Such disturbances can propagate to the end-effector and cause undesired motion, so the rejection of motor mount disturbances is also of interest. This thesis presents a strategy for measuring these disturbances and compensating for them. General approaches and implementation issues are explored qualitatively with a simple one-degree-of-freedom prototype (including a strategy for mitigating accelerometer drift), and quantitative simulation results are presented as a proof of concept.
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Rojas, Cristian R. "Robust Experiment Design." 2008. http://hdl.handle.net/1959.13/32293.
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Research Doctorate - Doctor of Philosophy (PhD)<br>This Thesis addresses the problem of robust experiment design, i.e., how to design an input signal to maximise the amount of information obtained from an experiment given limited prior knowledge of the true system. The majority of existing literature on experiment design specifically considers optimal experiment design, which, typically depends on the true system parameters, that is, the very thing that the experiment is intended to find. This obviously gives rise to a paradox. The results presented in this Thesis, on robust experiment design, are aimed at resolving this paradox. In the robust experiment design problem, we assume that the parameter vector is a-priori known to belong to a given compact set, and study the design of an input spectrum which maximises the worst case scenario over this set. We also analyse the problem from a different perspective where, given the same assumption on the parameter vector, we examine cost functions that give rise to an optimal input spectrum independent of the true system features. As a first approach to this problem we utilise an asymptotic (in model order) expression for the variance of the system transfer function estimator. To enable the extension of these results to finite order models, we digress from the main topic and develop several fundamental integral limitations on the variance of estimated parametric models. Based on these results, we then return to robust experiment design, where the input design problems are reformulated using the fundamental limitations as constraints. In this manner we establish that our previous results, obtained from asymptotic variance formulas, are valid also for finite order models. Robustness issues in experiment design also arise in the area of `identification for (robust) control'. In particular, a new paradigm has recently been developed to deal with experiment design for control, namely `least costly experiment design'. In the Thesis we analyse least costly experiment design and establish its equivalence with the standard formulation of experiment design problems. Next we examine a problem involving the cost of complexity in system identification. This problem consists of determining the minimum amount of input power required to estimate a given system with a prescribed degree of accuracy, measured as the maximum variance of its frequency response estimator over a given bandwidth. In particular, we study the dependence of this cost on the model order, the required accuracy, the noise variance and the size of the bandwidth of interest. Finally, we consider the practical problem of how to optimally generate an input signal given its spectrum. Our solution is centered around a Model Predictive Control (MPC) based algorithm, which is straightforward to implement and exhibits fast convergence that is empirically verified.
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YE, ZHAO-MING, and 葉昭明. "Robust two parameter control system design." Thesis, 1988. http://ndltd.ncl.edu.tw/handle/48502930673019231037.
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Hsu, Hsueh-Li, and 徐學禮. "A Robust Parameter Design in Continuous Intervals." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/29247139707120038332.
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碩士<br>國立屏東科技大學<br>工業管理系所<br>101<br>Parameter setting is an important procedure to design an effective and stable operation system. The most famous robust design is the Taguchi method. However the Taguchi method designs the optimal values only for operation parameters with ranges in several selectable levels but not in continuous areas. Currently, the response surface method and the Taguchi method with neural network techniques are the popular methods for setting parameters in continuous intervals. Both these two methods search the optimal operation setting based on derivative mathematical models. Thus, a wrong assumption for the mathematical model formation at the beginning will lead to a false optimal. Therefore, we develop a robust method for setting parameter in continuous intervals. The method will not need to assume the possible mathematical model formation at the beginning. Our idea is to introduce a simple operations research technique to work with the robust Taguchi method. This developed method performs the robust Taguchi process iteratively and use the operations research technique to improve the quality of each Taguchi result. This developed method will apply to search the parameter setting for optimizing the performance of a genetic algorithm. A practical integer programming problem, the Taiwan High Speed Rail scheduling problem, is used to test the performance of the genetic algorithm. The result shows that the proposed method improves the performance of the genetic algorithm and the result data show that this method is better than the popular response surface method.
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何文中. "Robust Design Optimization Using Parameter Variation Hyper Sphere." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/16017614424022993492.
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碩士<br>國立臺灣科技大學<br>機械工程技術研究所<br>86<br>This thesis addresses the constraint uncertainty and output deviation in the optimization processes due to the variation of design parameters in the product life cycle. Quality design seeks both the robustness of performance optimality and design feasibility. This research first elaborates the formulation of Parameter Variation Pattern (PVP). The PVP is then transformed to a Variation Hyper Sphere (VHS) to simplify the process of the constraint modification in the following robust optimization. The proposed methodology suggests a two-stage optimization scheme. After locating the nominal optimum, our scheme adopts the VHS to modify the feasible design region and applies the sequential approximate method (SLP/SQP) to accommodate the actyivity uncertainty due to parameter variation. The objective function is reformed to be the mean sum of squares of the difference between the nominal optimum output and the simulated scattered output using an orthogonal array. The revised window application ROP is then proposed for the facilitation of robust optimization.
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陳游利. "Robust deconvolution filter design under parameter and noise uncertainties." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/57823980854838589141.
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Govind, Nirmal. "Robust parameter design with imperfect experimental control of noise." 2004. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-482/index.html.
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Wu, Wei-Ming, and 吳偉銘. "Robust Parameter Design on the Cavity Characteristics of Supercavitation Torpedo." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/92178375834238455161.
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碩士<br>國防大學理工學院<br>兵器系統工程碩士班<br>99<br>The drag reduction for supercavitation is a new theory and approach that can conduct high-speed navigation of underwater vehicles. This mechanism of drag reduction is to generate a supercavity that can envelop the underwater vehicles, which would result in isolating the submerged body from water to avoid considerable frictional drag. A supercavity is influenced significantly by cavitator, many researches investigating the parametric effects of cavitator on supercavity have been proposed. However, most of these researches just paid attention on the effects of individual parameter; the assessments by using a systematized concept to integrate parameters are few. In this research, the software of computational fluid dynamics, Fluent 6.2, was used to simulate this study that is the steady, axis-symmetry natural supercavitation generated by cavitators with the types of cone, ellipse and trapezoid. The mixture multiphase model and the Singhal’s cavitation model were adopted to solve the RANS equation for the homogeneous supercavitation flow. The intelligent parameter design was implemented to obtain the best combination of multiquality characteristics that include length of supercavity, diameter of supercavity, and drag coefficient. In this work, we also used reduction percentage of quality loss (RPQL) to compare each optimum result. The effects of operating and environment factors were also taken into consideration. The results of simulation show that the underwater vehicle using supercavitation technology can obtain over 93% of drag reduction. Comparing the result by intelligent parametric design with the one by robust parametric design, the Principal Component Analysis’s reduction percentage of quality loss is 37.91% more than RPQL of Taguchi, for the intelligent parametric design, its reduction percentage of quality loss even increases up to 61.42%.
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XIA, YOU-LING, and 夏幼羚. "Robust design of two-parameter compensators in linear multivariable systems." Thesis, 1988. http://ndltd.ncl.edu.tw/handle/14452384374170071113.
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SU, JING-HUI, and 蘇景暉. "Parameter space methods for robust stability analysis and controller design." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/47979036347772939765.
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博士<br>國立臺灣大學<br>電機工程研究所<br>81<br>1 簡介
1.1 研究動機
1.2 強健穩定性的相關研究
1.3 強健控制的相關研究
1.4 論文內容的安排
2 連續系統的強健穩定性分析
2.1 問題的形成
2.2 主要成果
2.3 例題
3 離散系統的強健穩定性分析
3.1 系統的動態方程式
3.2 shift 模型的分析結果
3.3 delta 模型描述離散系統的分析結果
3.4 強健穩定區域的凸狀性質
3.5 例題
4 利用參數空間轉換來改善強健穩定分析的結果
4.1 系統的動態方程式
4.2 在參數空間上的座標轉換
4.3 最佳化問題
4.4 例題
5 參數空間上控制器的強化
5.1 系統的動態方程式
5.2 參數空間上的座標轉換與一強健穩定準則
5.3 強化的方法
5.4 例題
6 結論
附錄
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