Dissertations / Theses on the topic 'Observer based on emf estimation'

State estimation is an integral part of modern control techniques, as it allows to characterize the state information of complex plants based on a limited number of measurements and the knowledge of the process model. The benefit is twofold: on one hand it has the potential to rationalize the number of measurements required to monitor the plant, thus reducing costs, on the other hand it enables to extract information about variables that have an effect on the system but would otherwise be inaccessible to direct measurement. The scope of this thesis is to design a state estimator for a tubular copolymerization reactor, with the aim to provide the full state information of the plant and to characterize the quality of the product. Due to the fact that, with the existing set of measurements, only a small number of state variables can be observed, a new differential pressure sensor is installed in the plant to provide the missing information, and a model for the pressure measurement is developed. Following, the state estimation problem is approached rigorously and a comprehensive method for analyzing, tuning and implementing the state estimator is assembled from scientific literature, using a variety of tools from graph theory, linear observability theory and matrix algebra. Data reduction and visualization techniques are also employed to make sense of high dimensional information. The proposed method is then tested in simulations to assess the effect of the tuning parameters and measured set on the estimator performance during initialization and in case of estimation with plant-model mismatch. Finally, the state estimator is tested with plant data.

A control system is fault-tolerant if it possesses the capability of optimizing the system stability and admissible performance subject to bounded faults, complexity and modeling uncertainty. Based on this definition this thesis is concerned with the theoretical developments of the combination of robust fault estimation (FE) and robust active fault tolerant control (AFTC) for systems with both faults and uncertainties. This thesis develops robust strategies for AFTC involving a joint problem of on-line robust FE and robust adaptive control. The disturbances and modeling uncertainty affect the FE and FTC performance. Hence, the proposed robust observer-based fault estimator schemes are combined with several control methods to achieve the desired system performance and robust active fault tolerance. The controller approaches involve concepts of output feedback control, adaptive control, robust observer-based state feedback control. A new robust FE method has been developed initially to take into account the joint effect of both fault and disturbance signals, thereby rejecting the disturbances and enhancing the accuracy of the fault estimation. This is then extended to encompass the robustness with respect to modeling uncertainty. As an extension to the robust FE and FTC scheme a further development is made for direct application to smooth non-linear systems via the use of linear parameter-varying systems (LPV) modeling. The main contributions of the research are thus: - The development of a robust observer-based FE method and integration design for the FE and AFTC systems with the bounded time derivative fault magnitudes, providing the solution based on linear matrix inequality (LMI) methodology. A stability proof for the integrated design of the robust FE within the FTC system. - An improvement is given to the proposed robust observer-based FE method and integrated design for FE and AFTC systems under the existence of different disturbance structures. - New guidance for the choice of learning rate of the robust FE algorithm. - Some improvement compared with the recent literature by considering the FTC problem in a more general way, for example by using LPV modeling.

New system technologies are continuously improving the performance of vehicles with regard to safety, comfort, stability and the environment. The development of control systems based on anti-lock braking system, active steering control, adaptive cruise control, collision avoidance, electronic stability programme or roll-over prevention systems, facilitated these improvements. In order to maximise the benefits from such devices, information about the tyre/road friction parameter is required in real-time. As it is impractical to measure the tyre/road friction coefficient, estimation from other available parameters is essential. In this thesis, the main theoretical contribution is the development of sliding mode schemes for tyre/road friction estimation. In the first part of this thesis, a sliding mode based scheme is designed for a braking scenario. The scheme is designed to maintain the longitudinal slip value associated with the tyre road contact patch at an optimum value utilising a sliding mode controller, subject to varying road conditions. The stability of the controller is proven using a Lyapunov function and Linear Matrix Inequality (LMI) method. An analysis of the designed scheme in the presence of imperfect measurement of wheel angular velocity is also presented. The sliding mode scheme is also compared with an adaptive scheme from the literature. The comparison study shows that the sliding mode based scheme appears more robust than the adaptive scheme, and the simulation results are supported by the analysis. Another key contributions in this thesis is the development of a sliding mode based scheme which is independent of the underlying friction model. This distinguishes the work proposed in this thesis from the existing literature. Finally a comparative study is presented for the observers considered in this thesis using three different friction models. The results for different road conditions show that the sliding mode based schemes out-perform the adaptive scheme for the tests undertaken.

Characterisation of modern complex powertrains is a time consuming and expensive process. Little effort has been made to improve the efficiency of testing methodologies used to obtain data for this purpose. Steady-state engine testing is still regarded as the golden standard, where approximately 90% of testing time is wasted waiting for the engine to stabilize. Rapid dynamic engine testing, as a replacement for the conventional steady-state method, has the potential to significantly reduce the time required for characterisation. However, even by using state of the art measurement equipment, dynamic engine testing introduces the problem that certain variables are not directly measurable due to the excitation of the system dynamics. Consequently, it is necessary to develop methods that allow the observation of not directly measurable quantities during transient engine testing. Engine testing for the characterisation of the engine air-path is specifically affected by this problem since the air mass flow entering the cylinder is not directly measurable by any sensor during transient operation. This dissertation presents a comprehensive methodology for engine air charge characterisation using dynamic test data. An observer is developed, which allows observation of the actual air mass flow into the engine during transient operation. The observer is integrated into a dual-ramp testing procedure, which allows the elimination of unaccounted dynamic effects by averaging over the resulting hysteresis. A simulation study on a 1-D gas dynamic engine model investigates the accuracy of the developed methodology. The simulation results show a trade-off between time saving and accuracy. Experimental test result confirm a time saving of 95% compared to conventional steady-state testing and at least 65% compared to quasi steady-state testing while maintaining the accuracy and repeatability of conventional steady-state testing.

The main focus of the study is the implementation of techniques regarding flux estimation and rotor speed estimation by the use of sensorless closed-loop observers. Within this framework, the information about the mathematical representation of the induction motor, pulse width modulation technique and flux oriented vector control techniques together with speed adaptive flux estimation &ndash
a kind of sensorless closed loop estimation technique- and Kalman filters is given. With the comparison of sensorless closed-loop speed estimation techniques, it has been attempted to identify their superiority and inferiority to each other by the use of simulation models and real-time experiments. In the experiments, the performance of the techniques developed and used in the thesis has been examined under extensively changing speed and load conditions. The real-time experiments have been carried out by the use of TI TMS320F2812 digital signal processor, XILINX XCS2S150E Field Programmable Gate Array (FPGA), control card and the motor drive card Furthermore, Matlab &ldquo
Embedded Target for the TI C2000 DSP&rdquo
and &ldquo
Code Composer Studio&rdquo
software tools have been used. The simulations and experiments conducted in the study have illustrated that it is possible to increase the performance at low speeds at the expense of increased computational burden on the processor. However, in order to control the motor at zero speed, high frequency signal implementation should be used as well as a different electronic hardware.

Cette thèse s'inscrit dans le cadre du projet Compacité qui vise à développer un compresseur électrique pour véhicules électriques à l’aide d’une démarche mécatronique. Dans cette thématique, le rôle du LGEP est de développer la partie électromécanique du compresseur. Cette thèse est constituée de deux parties, la première concerne la conception d’un moteur pour le compresseur et la deuxième a trait à la commande sans capteur mécanique de ce moteur. La première partie de la thèse est d'abord consacrée au dimensionnement d'une machine électrique pour un compresseur électrique. Le cahier des charges impose une machine compacte (97mm de diamètre et une profondeur inférieure à 50mm) et ayant une puissance massique élevée (6kW pour une masse de 1.8kg). Au préalable, un modèle analytique a été développé pour effectuer un dimensionnement rapide. Par la suite, la méthode des éléments finis a été appliquée à différents modèles physiques (magnétique, thermique, mécanique (résistance des matériaux et vibration)) pour une étude approfondie de la structure choisie. A l'issue de ces études, un prototype et un banc expérimental ont été réalisés. Dans un second temps, des algorithmes de commande avec ou sans capteur mécanique ont été étudiés pour le pilotage du moteur. La particularité de cette deuxième partie de thèse est la réalisation d'une commande peu gourmande en temps de calcul et implantable dans des microcontrôleurs de faibles performances. A l'issue de cette partie, une nouvelle loi de commande appelée commande passive échantillonnée ainsi qu'un observateur adaptatif étendu (observateur fondé sur l'estimation des fem) ont été développés et testés sur un banc expérimental
This thesis is part of the project Compacite which aims to develop an electric compressor for electrical vehicles using a mechatronic approach. In this way, the LGEP contribution is to develop the electromechanical part of the compressor.The document is divided in two parts: the first one is related to the design of the motor and the second part is dedicated to the sensorless control.In the first part, the electromagnetic design is proposed to comply with the industrial constraints according to the compressor operation. The specifications require a compact motor (external diameter equal to 97 mm and an active depth less than 50 mm) and a good power/mass ratio (6 kW for a weight of 1.8 kg). At first the design is based on an analytical model in order to obtain a fast sizing. Thereafter the finite element method is used for multiphysical studies (magnetic, thermal and mechanical (in terms of strength of materials and vibration)). A prototype is built and characterized on a test bench. In the second part, some algorithmic control laws have been developed with sensor and sensorless control. In this part a particular control law (sampled data passivity based control) with a low algorithmic cost has been developed for driven the motor and has been validated on the test bench. At the end an observer based on the estimation of the electromotive force is used for sensorless control and validated on the test bench

Ce mémoire de thèse est consacré à la conception de méthodes de diagnostic à base de modèles fondées sur les observateurs pour les systèmes non linéaires modélisés comme des systèmes singuliers (D) linéaires à paramètres variants (LPV), notés D-LPV (Descriptor-Linear Parameter Varying). Les systèmes D-LPV constituent une classe particulière de systèmes approximant avec un certain degré de précision la dynamique des systèmes complexes non linéaires à partir d’une combinaison de modèles linéaires locaux pondérés par des fonctions convexes d'ordonnancement. Dans le contexte de l’apparition de défauts capteurs ou actionneurs, ce travail de thèse s’attache aux systèmes pour lesquels ces fonctions d'ordonnancement sont non mesurables mais dépendent de l'état du système. Afin de détecter et isoler des défauts, ce travail de thèse développe des synthèses d'observateurs appropriés en développant des nouvelles conditions suffisantes en termes d’inégalités matricielles linéaires (LMI) pour garantir la synthèse de résidus sensibles aux défauts et robustes aux erreurs d’estimation inhérentes aux fonctions d'ordonnancement non mesurables. - Étendant des méthodes H∞ afin d’effectuer l'estimation d'état, la détection de pannes, la localisation et la reconstruction de défaut sur les capteurs ; - Garantissant une sensibilité “optimale” aux pannes vis-À-Vis du rejet de perturbations au travers le développement d’observateurs de type H_/H∞. À cette fin, le mémoire de thèse est organisé en cinq chapitres : Le Chapitre 1 est consacré à l’introduction générale, aux objectifs et contributions de ce travail. Le Chapitre 2 présente les éléments nécessaires pour décrire la représentation, la modélisation, les propriétés, l'analyse et la conception d'observateur pour les systèmes D-LPV ainsi qu’un état de l’art détaillé des travaux associés à ce thème de recherche. Le Chapitre 3 est dédié au développement de trois méthodes différentes fondées sur la théorie H∞ pour concevoir des observateurs de détection de défaut pour les systèmes D-LPV. Les méthodes proposées sont appliquées à un exemple dans le cadre de la détection de défaut capteurs. L’isolation de ces défauts est mise en œuvre au travers un banc d’observateurs et les performances de chacune des trois méthodes sont comparées. Le Chapitre 4 propose une méthode de détection de défauts sur la base d’observateurs établis sur le principe H_/H∞, tenant compte ainsi d'un meilleur compromis entre la sensibilité aux pannes et la robustesse aux perturbations. De nouvelles conditions suffisantes à l’aide de LMI sont proposées afin de résoudre le problème de synthèse du gain des observateurs. Le dernier chapitre est dédié à la conclusion générale et à l’analyse de problèmes ouverts pouvant être abordés dans des travaux futurs
This work is dedicated to the synthesis of model-Based fault detection and isolation (FDI) techniques based on observers for nonlinear systems modeled as Descriptor-Linear Parameter Varying (D-LPV) systems. D-LPV systems are a particular class of systems that can represent (or approximate in some degree of accuracy), complex nonlinear systems by a set of linear local models blended through convex parameter-Dependent scheduling functions. The global D-LPV System can describe both time-Varying and nonlinear behavior. Nevertheless, in many applications the time-Varying parameters in the scheduling functions could be unmeasurable. Models which depend on unmeasurable scheduling functions cover a wide class of nonlinear systems compared to models with measurable scheduling functions, but the design of control schemes for D-LPV systems with unmeasurable scheduling functions are more difficult than those with a measurable one, because the design of such control schemes involve the estimation of the scheduling vector. This topic is addressed in this work by considering the following main targets: • to design FDI in D-LPV systems based on -H∞ observers in order to guarantee robustness against disturbances and errors due the unmeasurable gain scheduling functions • to extend the proposed -H∞ methods to perform state estimation and fault detection, isolation and fault magnitude estimation in the case of sensor faults • to guarantee the best trade-Off between fault sensitivity and disturbance rejection by developing H_/H∞ fault detection observers for D-LPV systems. The thesis is organized as follows Chapter 1 is dedicated to provide a general introduction, the objectives and contribution of this work.Chapter 2 is organized in order to provide the minimum necessary elements to describe the representation, modeling, properties, analysis, and observer design of D-LPV systems. Chapter 2 is also dedicated to a detailed review of the state of the art. Chapter 3 is dedicated to the development of three different methods to design fault detection observers for D-LPV systems based on H∞ theory. Finally, the proposed methods are applied to an example, for sensor fault detection and isolation by means of an observer bank, in order to compare the performance of each method. Chapter 4 is dedicated to the design of a FDI method based on observers with H_/H∞ performance. Based on the H_/H∞ approach, which considers the best trade-Off between fault sensitivity and robustness to disturbance, adequate LMIs are obtained to guarantee sufficient conditions for the design problem. In order to illustrate the effectiveness of the proposed techniques, an example is considered

Fault detection and diagnosis have gained central importance in the chemical process industries over the past decade. This is due to several reasons, one of them being that copious amount of data is available from a large number of sensors in process plants. Moreover, since industrial processes operate in closed loop with appropriate output feedback to attain certain performance objectives, instrument faults have a direct effect on the overall performance of the automation system. Extracting essential information about the state of the system and processing the measurements for detecting, discriminating, and identifying abnormal readings are important tasks of a fault diagnosis system. The goal of this dissertation is to develop such fault diagnosis systems, which use limited information about the process model to robustly detect, discriminate, and reconstruct instrumentation faults. Broadly, the proposed method consists of a novel nonlinear state and parameter estimator coupled with a fault detection, discrimination, and reconstruction system. The first part of this dissertation focuses on designing fault diagnosis systems that not only perform fault detection and isolation but also estimate the shape and size of the unknown instrument faults. This notion is extended to nonlinear processes whose structure is known but the parameters of the process are a priori uncertain and bounded. Since the uncertainty in the process model and instrument fault detection interact with each other, a novel two-time scale procedure is adopted to render overall fault diagnosis. Further, some techniques to enhance the convergence properties of the proposed state and parameter estimator are presented. The remaining part of the dissertation extends the proposed model-based fault diagnosis methodology to processes for which first principles modeling is either expensive or infeasible. This is achieved by using an empirical model identification technique called subspace identification for state-space characterization of the process. Finally the proposed methodology for fault diagnosis has been applied in numerical simulations to a non-isothermal CSTR (continuous stirred tank reactor), an industrial melter process, and a debutanizer plant.

Les travaux de cette thèse portent sur l’estimation et la commande décentralisée des systèmes de grande dimension. L’objectif est de développer des capteurs logiciels pouvant produire une estimation fiable des variables nécessaires pour la stabilisation des systèmes non linéaires interconnectés. Une décomposition d’un tel système de grande dimension en un ensemble de n sous-systèmes interconnectés est primordiale. Ensuite, en tenant compte de la nature du sous-système ainsi que les fonctions d’interconnexions, des lois de commande décentralisées basées observateurs ont été synthétisées. Chaque loi de commande est associée à un sous-système qui permet de le stabiliser localement, ainsi la stabilité du système global est assurée. L’existence d’un observateur et d’un contrôleur stabilisant le système dépend de la faisabilité d’un problème d’optimisation LMI. La formulation LMI, basée sur l’approche de Lyapunov, est élaborée par l’utilisation de principe de DMVT sur la fonction d’interconnexion non linéaire supposée bornée et incertaine. Ainsi des conditions de synthèse non restrictives sont obtenues. Des méthodes de synthèse de loi de commande décentralisée basée observateur ont été proposées pour les systèmes non linéaires interconnectés dans le cas continu et dans le cas discret. Des lois de commande robuste H1 décentralisées sont élaborées pour les systèmes non linéaires interconnectés en présence de perturbations et des incertitudes paramétriques. L’efficacité et la validation des approches présentées sont testées sur un modèle de réseaux électriques composé de trois générateurs interconnectés
This thesis focuses on the decentralized estimation and control for large scale systems. The objective is to develop software sensors that can produce a reliable estimate of the variables necessary for the interconnected nonlinear systems stability analysis. A decomposition of a such large system into a set of n interconnected subsystems is paramount for model simplification. Then, taking into account the nature of the subsystem as well as the interconnected functions, observer-based decentralized control laws have been synthesized. Each control law is associated with a subsystem which allows it to be locally stable, thus the stability of the overall system is ensured. The existence of an observer and a controller gain matrix stabilizing the system depends on the feasibility of an LMI optimization problem. The LMI formulation, based on Lyapunov approach, is elaborated by applying the DMVT technique on the nonlinear interconnection function, assumed to be bounded and uncertain. Thus, non-restrictive synthesis conditions are obtained. Observer-based decentralized control schemes have been proposed for nonlinear interconnected systems in the continuous and discrete time. Robust Hinfini decentralized controllers are provided for interconnected nonlinear systems in the presence of perturbations and parametric uncertainties. Effectiveness of the proposed schemes are verified through simulation results on a power systems with interconnected machines

Ce travail de recherche propose le développement et la validation d’une méthode de prédiction in-situ et temps réel de la durée de vie utile restante des engrenages de boîtes de vitesses automobiles de série. Cette méthode est destinée à être implantée dans des unités de commande électronique standards. En s’attachant tout particulièrement à proposer une solution simple, fiable, rentable et facilement transposable pour tout type de configuration, le système se base sur la combinaison d’une méthode d’acquisition des couples agissants sur la boîte de vitesses et d’une estimation continue des niveaux d’endommagement des engrenages. Un état de l’art et les fondamentaux théoriques d’une estimation de l’endommagement par une approche de contrainte nominale et une accumulation linéaire des endommagements partiels sont abordés dans un premier temps. La structure globale de l’algorithme de calcul de l’endommagement est ensuite étudiée et l’approche méthodologique adoptée pour sa mise au point expliquée. Cette dernière repose en grande partie sur un modèle complet de véhicule valide par des essais sur route et des mesures, où une attention toute particulière est portée à la représentation des changements de rapport et de la dynamique de la boîte de vitesses. Deux types de boite de vitesses sont alors considérées, une boite manuelle standard et une boite à double embrayage, et une spécification technique pour la configuration de l’algorithme ainsi qu’une analyse des besoins pour la méthode d’acquisition des couples sont formulées. En se basant sur ces études, un observateur d’état capable de reconstruire le couple agissant sur les disques d’embrayage ainsi que le couple en sortie de boite est développé et valide. Finalement, une synthèse de la méthode complète et de l’algorithme final est adressée, et les avantages économiques et écologiques liés à l’introduction de cette méthode pour des mesures de conception légère des boîtes de vitesses automobiles sont abordés et évalués
This research work proposes the development and the validation of an online and real-time method to predict the remaining service life of the gearwheels of automotive transmissions, with the aim of implementing it on standard control units of series-production vehicles. By focusing on the proposition of a simple, reliable and easy-to-implement solution, the system relies on the combination of an acquisition method of the torques acting in the transmission and a continuous estimation of the damage levels of the gearwheels. Firstly, a state of the art and the theoretical basics are presented concerning a damage estimation based on a nominal stress concept and a linear damage accumulation. The global structure of the damage estimation algorithm is then analyzed and the methodological approach adopted for its development is explained. This is based in principal on a drivetrain model, validated with tests and measurements, where a particular attention is paid to the representation of the gear shifts and the transmission dynamics. Two types of transmissions are considered, namely a standard manual transmission and a dual clutch transmission mounted in series-production cars. Respectively a requirement analysis for the configuration of the algorithm as well as a requirement specification for the torque acquisition method are performed. On this basis, a state observer is developed and validated, which is able to reconstruct the clutch torque and the transmission output torque. Finally, a synthesis of the complete method and the final version of the algorithm are addressed, and the economic and ecological advantages of the introduction of the method in the context of lightweight design measures are discussed and evaluated
Kurzfassung Diese Dissertation beschreibt die Entwicklung einer Online- und Echtzeit-Methode zur Vorhersage der restlichen Lebensdauer von den Zahnradern eines Kraftfahrzeuggetriebes. Diese Methode ist fur eine Implementierung auf Standard-Steuergeraten vorgesehen. Durch die Fokussierung auf eine einfache, zuverlassige und leicht zu implementierende Losung beruht die Methode auf der Kombination aus einer Drehmomenterfassungsmethode und einer kontinuierlichen Vorhersage des Schadigungsniveaus der Zahnrader. Zuerst werden der Stand der Technik und die theoretischen Grundlagen von Schadigungsberechnungen basierend auf dem Nennspannungskonzept und einer linearen Schadensakkumulation dargestellt. Danach wird die globale Struktur des Schadigungsberechnungsalgorithmus gezeigt und die fur die Entwicklung ausgewahlte methodische Vorgehensweise erlautert. Diese bezieht sich grundsatzlich auf ein durch Testfahrten und Messungen verifiziertes Antriebsstrangmodell, welches besonders die Schaltungen und die Dynamik des Getriebes berucksichtigt. Ein Serien-Handschaltgetriebe und ein Serien-Doppelkupplungsgetriebe werden betrachtet. Fur diese zwei Getriebetypen werden eine Anforderungsanalyse zur Konfiguration des Algorithmus sowie eine Anforderungsspezifikation fur die Drehmomenterfassungsmethode durchgefuhrt. Auf Basis dieser Untersuchungen wird dann ein Zustandsbeobachter zur Rekonstruktion des Kupplungs- und Getriebeausgangsdrehmoments entwickelt und validiert. Infolgedessen werden eine Synthese der kompletten Methode und die Endversion des Algorithmus vorgestellt. Abschliesend werden die Wirtschaftlichkeit sowie die okologischen Vorteile in Bezug auf die Einfuhrung der Lebensdauermonitoringmethode im Rahmen von Leichtbaumasnahmen diskutiert und bewertet

Recently, a lot of research work has been dedicated toward enhancing performance, reliability and integrity of distributed energy resources that are integrated into distribution networks. The problem of islanding detection and islanding prevention (i.e. anti-islanding) has stimulated a lot of research due to its role in severely compromising the safety of working personnel and resulting in equipment damages. Various Islanding Detection Methods (IDMs) have been developed within the last ten years in anticipation of the tremendous increase in the penetration of Distributed Generation (DG) in distribution system. This work proposes new IDMs that rely on transient and distributed behaviors to improve integrity and performance of DGs while maintaining multi-DG islanding detection capability. In this thesis, the following questions have been addressed: How to utilize the transient behavior arising from an islanding condition to improve detectability and robust performance of IDMs in a distributive manner? How to reduce the negative stability impact of the well-known Sandia Frequency Shift (SFS) IDM while maintaining its islanding detection capability? How to incorporate the perturbations provided by each of DGs in such a way that the negative interference of different IDMs is minimized without the need of any type of communication among the different DGs? It is shown that the proposed techniques are local, scalable and robust against different loading conditions and topology changes. Also, the proposed techniques can successfully distinguish an islanding condition from other disturbances that may occur in power system networks. This work improves the efficiency, reliability and safety of integrated DGs, which presents a necessary advance toward making electric power grids a smart grid.
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering

Dans un objectif conjoint d'identification paramétrique en ligne, les méthodes développées dans cette thèse permettent de concevoir en ligne et en boucle fermée les entrées optimales qui enrichissent les informations contenues dans l'expérience en cours. Ces méthodes reposent sur des mesures en temps réel du procédé, sur un modèle dynamique non linéaire (ou linéaire) multi-variable choisi du procédé, sur un modèle de sensibilité des mesures par rapport aux paramètres à estimer et sur un observateur non linéaire. L'analyse de l'observabilité et des techniques de commande prédictive permettent de définir la commande optimale qui est déterminée en ligne par optimisation sous contraintes. Des aspects de stabilisation sont également étudiés (via un apport de contraintes fictives ou via une technique de Lyapunov). Enfin, une loi de commande explicite pour le cas particulier du système d'ordre un est développée. Des exemples illustratifs sont traités via le logiciel ODOE4OPE : un bioréacteur, un réacteur continu parfaitement agité et une aile delta. Ces exemples permettent de voir que l'estimation des paramètres peut être réalisée avec une bonne précision, et à moindre coût expérimental en une expérience
For online parameter identification, the developed methods here allow to design online and in closed loop optimal inputs that enrich the information in the current experience. These methods are based on real-time measurements of the process, on a dynamic nonlinear (or linear) multi-variable model, on a sensitivity model of measurements with respect to the parameters to be estimated and a nonlinear observer. Analysis of observability and predictive control techniques are used to define the optimal control which is determined online by constrained optimization. Stabilization aspects are also studied (by adding fictitious constraints or by a Lyapunov technique). Finally, for the particular case of a first order linear system, the explicit control law is developed. Illustrative examples are processed via the ODOE4OPE software : a bio-reactor, a continuous stirred tank reactor and a delta wing. These examples help to see that the parameter estimation can be performed with good accuracy in a single and less costly experiment

碩士
國立臺灣大學
機械工程學研究所
101
This thesis proposes a self-sensing method based, combining the equivalent-EMF method and tracking observer, for PMSMs, and this method can be applied for medium and high-speed operation. The terms of equivalent EMF are obtained by equivalent-EMF method, and are used as the input of tracking observer. Afterward the estimated electrical rotor position and rotor speed can be obtained by tracking observer. The proposed method in this thesis successfully eliminates the phase-lag properties result from the LPF which is added into the equivalent-EMF method, and improves the equivalent-EMF method’s performance. The experimental results show that the steady-state and transient response of the proposed method are good, and the performance is better than extended-EMF method’s.

Issues pertaining to the control of a rigid body are considered in this work. A magnetically levitated robotic wrist is here modelled as a rigid body subjected to both control and environment forces. All the algorithms presented here were implemented on the Maglev wrist for experimental verification. A good inertial model of the rigid body was needed for the estimation and control work in this work; a least squares identification procedure, found in the literature, was implemented for this purpose. Algorithms are developed for obtaining dynamic environment force and torque estimates from position errors in a velocity observer. Obtaining torque estimates from a nonlinear velocity observer is achieved by using the linear force observer as an analogue. Stability of the torque observer to a constant environment torque is proven for the one dimensional case only. Simulation and experiments are used to verify the stability in the three dimensional case. Environment force/torque measurements, alone useful for control purposes, are also used to correct a velocity observer. The resulting corrected observer design gives low noise velocity estimates and is robust in that it is not sensitive to errors caused by interaction with the environment. As a demonstration of the merit of the observer based work, a remote center of compliance controller is implemented. An inertial model is needed to provide feedforward that linearizes the dynamics to a. second order system. Corrected observer velocities are used in the feedforward and the derivative component of the control law. The linear dynamics about a remote center is verified by comparing the environment forces measured with the velocities observed.

A recording of the defense presentation for this dissertation is available at: http://hdl.handle.net/10754/625197
Steady-state elliptic partial differential equations (PDEs) are frequently used to model a diverse range of physical phenomena. The source and boundary data estimation problems for such PDE systems are of prime interest in various engineering disciplines including biomedical engineering, mechanics of materials and earth sciences. Almost all existing solution strategies for such problems can be broadly classified as optimization-based techniques, which are computationally heavy especially when the problems are formulated on higher dimensional space domains. However, in this dissertation, feedback based state estimation algorithms, known as state observers, are developed to solve such steady-state problems using one of the space variables as time-like. In this regard, first, an iterative observer algorithm is developed that sweeps over regular-shaped domains and solves boundary estimation problems for steady-state Laplace equation. It is well-known that source and boundary estimation problems for the elliptic PDEs are highly sensitive to noise in the data. For this, an optimal iterative observer algorithm, which is a robust counterpart of the iterative observer, is presented to tackle the ill-posedness due to noise. The iterative observer algorithm and the optimal iterative algorithm are then used to solve source localization and estimation problems for Poisson equation for noise-free and noisy data cases respectively. Next, a divide and conquer approach is developed for three-dimensional domains with two congruent parallel surfaces to solve the boundary and the source data estimation problems for the steady-state Laplace and Poisson kind of systems respectively. Theoretical results are shown using a functional analysis framework, and consistent numerical simulation results are presented for several test cases using finite difference discretization schemes.

碩士
大同大學
電機工程學系(所)
93
In this thesis, an observer-based adaptive fuzzy control method for uncertain single-input single-output nonlinear dynamical systems with unknown nonlinearities is proposed. The unknown nonlinearities are approximated by the fuzzy logic system whose parameters can be adjusted on-line according to some adaptive laws for the purpose of controlling the output of the nonlinear system to track a given trajectory. The proposed method need not the assumption that the state variables full observability, and does also not require any priori knowledge of the upper bounds on the uncertainties including approximations errors and external disturbances. And the state variables can be estimated by designing the observer. The Lyapunov stability theory is used to guarantee a uniformly ultimately bounded for the state estimation error and tracking error as well as all other signals in the closed-loop system. Finally, the proposed method is applied to control some examples of nonlinear systems and simulation results demonstrate the effectiveness of the control scheme.

碩士
輔仁大學
電子工程學系
94
This paper proposes an antilock braking system (ABS), in which unknown road characteristics are resolved by a road estimator. This estimator is based on the LuGre friction model with a road condition parameter, and can transmit a reference slip ratio to a slip ratio controller through a mapping function. A feedforward neural networks using back-propagation learning algorithm is used to identify the mapping function from road characteristics to reference slip ratios. Besides, we further adopt a wheel velocity and the road condition parameter to be the inputs of three dimension mapping function to reduce braking time. The slip ratio controller is used to maintain the slip ratio of the wheel at the reference values for various road surfaces. In the controller design, an observer-based direct adaptive fuzzy-neural controller (DAFC) for an ABS is developed to on-line tune the weighting factors of the controller under the assumption that only the wheel slip ratio is available. Finally, this paper gives simulation results to provide good effectiveness under varying road conditions.

This dissertation addresses novel techniques in determining gyroless micro-satellite attitude and attitude rate. The main objective of this thesis is to explore the possibility of using commercially available low cost micro-light star sensor as a stand-alone sensor for micro-satellite attitude as well as attitude rate determination. The objective is achieved by developing accurate and computationally efficient algorithms for the realization of onboard operation of a low fidelity star sensor. All the algorithms developed here are tested with the measurement noise presented in the catalog of the sensor array STAR-1000. A novel accurate second order sliding mode observer (SOSMO) is designed for discrete time uncertain linear multi-output system. Our design procedure is effective for both matched and unmatched bounded uncertain ties and/or disturbances. The bound on uncertainties and/or disturbances is assumed to be unknown. This problem is addressed in this work using the second order multiple sliding modes approach. Second order sliding manifold and corresponding sliding condition for discrete time system is defined similar on the lines of continuous counterpart. Our design is not restricted to a particular class of uncertain (matched) discrete time system. Moreover, it can handle multiple outputs unlike single out-put systems. The observer design is achieved by driving the state observation error and its first order finite difference to the vicinity of the equilibrium point (0,0) in a finite steps and maintaining them in the neighborhood thereafter. The estimation synthesis is based on Quasi Sliding Mode (QSM) design. The problem of designing sliding mode observer for a linear system subjected to unknown inputs requires observer matching condition. This condition is needed to ensure that the state estimation error is a asymptotically stable and is independent of the unknown input during the sliding motion. In the absence of a matching condition, asymptotic stability of the reduced order error dynamics on the sliding surface is not guaranteed. However, unknown bounded inputs guarantee bounded error on state estimation. The QSM design guarantees an ultimate error bound by incorporating Boundary Layer (BL) in its design procedure. The observer achieves one order of magnitude improvement in estimation accuracy than the conventional sliding mode observer (SMO) design for an unknown input. The observer estimation errors, satisfying the given stability conditions, converge to an ultimate finite bound (with in the specified BL) of O(T2), where T Is the sampling period. A relation between sliding mode gain and boundary layer is established for the existence of second order discrete sliding motion. The robustness of the proposed observer with respect to measurement noise is also analyzed. The design algorithm is very simple to apply and is implemented for two examples with different classes of disturbances (matched and unmatched) to show the effectiveness of the design. Simulation results show the robustness with respect to the measurement noise for SOSMO. Second order sliding mode observer gain can be calculated off-line and the same gain can work for large band of disturbance as long as the disturbance acting on the continuous time system is bounded and smooth. The SOSMO is simpler to implement on board compared to the other traditional nonlinear filters like Pseudo-Linear-Kalman-filter(PLKF); Extended Kalman Filter(EKF). Moreover, SMO possesses an automatic adaptation property same as optimal state estimator(like Kalman filter) with respect to the intensity of the measurement noise. The SMO rejects the noisy measurements automatically, in response to the increased noise intensity. The dynamic performance of the observer on the sliding surface can be altered and no knowledge of noise statistics is required. It is shown that the SOSMO performs more accurately than the PLKF in application to micro-satellite angular rate estimation since PLKF is not an optimal filter. A new method for estimation of satellite angular rates through derivative approach is proposed. The method is based on optic flow of star image patterns formed on a star sensor. The satellite angular rates are derived directly from the 2D-coordinates of star images. Our algorithm is computationally efficient and requires less memory allocation compared to the existing vector derivative approaches, where there is also no need for star identification. The angular rates are computed using least square solution method, based on the measurement equation obtained by optic flow of star images. These estimates are then fed into discrete time second order sliding mode observer (SOSMO). The performance of angular rate estimation by SOSMO is compared with the discrete time First order SMO and PLKF. The SOSMO gives the best estimates as compared to the other two schemes in estimating micro-satellite angular rates in all three axes. The improvement in accuracy is one order of magnitude (around1.7984 x 10−5 rad/ sec,8.9987 x 10−6 rad/ sec and1.4222 x 10−5 rad/ sec in three body axes respectively) in terms of standard deviation in steady state estimation error. A new method and algorithm is presented to determine star camera parameters along with satellite attitude with high precision even if these parameters change during long on-orbit operation. Star camera parameters and attitude need to be determined independent of each other as they both can change. An efficient, closed form solution method is developed to estimate star camera parameters (like focal length, principal point offset), lens distortions (like radial distortion) and attitude. The method is based on a two step procedure. In the first step, all parameters (except lens distortion) are estimated using a distortion free camera model. In the second step, lens distortion coefficient is estimated by linear least squares (LS) method. Here the derived camera parameters in first step are used in the camera model that incorporates distortion. However, this method requires identification of observed stars with the catalogue stars. But, on-orbit star identification is difficult as it utilizes the values of camera calibrating parameters that can change in orbit(detector and optical element alignment get change in orbit due to solar pressure or sudden temperature change) from the ground calibrated value. This difficulty is overcome by employing a camera self-calibration technique which only requires four observed stars in three consecutive image frames. Star camera parameters along with lens (radial and decentering) distortion coefficients are determined by camera self calibration technique. Finally Kalman filter is used to refine the estimated data obtained from the LS based method to improve the level of accuracy. We consider the true values of camera parameters as (u0,v0) = (512.75,511.25) pixel, f = 50.5mm; The ground calibrated values of those parameters are (u0,v0) =( 512,512) pixel, f = 50mm; Worst case radial distortion coefficient affecting the star camera lens is considered to be k1 =5 x 10−3 .Our proposed method of attitude determination achieves accuracy of the order of magnitude around 6.2288 x 10−5 rad,3.3712 x 10−5 radand5.8205 x 10−5 rad in attitude angles φ,θ and ψ. Attitude estimation by existing methods in the literature diverges from the true value since they utilize the ground calibrated values of camera parameters instead of true values. To summarize, we developed a formal theory of discrete time Second Order Sliding Mode Observer for uncertain multi-output system. Our methods achieve the desired accuracy while estimating satellite attitude and attitude rate using low fidelity star sensor data. Our methods require lower on-board processing requirement and less memory allocation; thus are suitable for micro-satellite applications. Thus, the objective of using low fidelity star sensor as stand-alone sensor in micro-satellite application is achieved.

Indiana University-Purdue University Indianapolis (IUPUI)
A gradient free function optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized in parameter identification of the electrochemical model of a Lithium-Ion battery having a LiCoO2 chemistry. Battery electrochemical model parameters are subject to change under severe or abusive operating conditions resulting in, for example, Navy over-discharged battery, 24-hr over-discharged battery, and over-charged battery. It is important for a battery management system to have these parameters changes fully captured in a bank of battery models that can be used to monitor battery conditions in real time. In this work, PSO methodology has been used to identify four electrochemical model parameters that exhibit significant variations under severe operating conditions. The identified battery models were validated by comparing the model output voltage with the experimental output voltage for the stated operating conditions. These identified conditions of the battery were then used to monitor condition of the battery that can aid the battery management system (BMS) in improving overall performance. An adaptive estimation technique, namely multiple model adaptive estimation (MMAE) method, was implemented for this purpose. In this estimation algorithm, all the identified models were simulated for a battery current input profile extracted from the hybrid pulse power characterization (HPPC) cycle simulation of a hybrid electric vehicle (HEV). A partial differential algebraic equation (PDAE) observer was utilized to obtain the estimated voltage, which was used to generate the residuals. Analysis of these residuals through MMAE provided the probability of matching the current battery operating condition to that of one of the identified models. Simulation results show that the proposed model based method offered an accurate and effective fault diagnosis of the battery conditions. This type of fault diagnosis, which is based on the models capturing true physics of the battery electrochemistry, can lead to a more accurate and robust battery fault diagnosis and help BMS take appropriate steps to prevent battery operation in any of the stated severe or abusive conditions.