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Relevant bibliographies by topics / System Linearization

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Academic literature on the topic 'System Linearization'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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Journal articles on the topic "System Linearization"

1

Bist, Avisek, and Namita Behera. "Fiedler linearizations of multivariable state-space systems and its associated system matrix." Filomat 38, no. 32 (2024): 11275–94. https://doi.org/10.2298/fil2432275b.

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Linearization is a standard method in the computation of eigenvalues and eigenvectors of matrix polynomials. In the last decade a variety of linearization methods have been developed in order to deal with algebraic structures and in order to construct efficient numerical methods. An important source of linearizations for matrix polynomials are the so called Fiedler pencils, which are generalizations of the Frobenius companion form and these linearizations have been extended to regular rational matrix function which is the transfer function of LTI State-space system in [20, 25]. We consider a m

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2

Chao, Kao-Shing Hwang, Horng-Jen. "REINFORCEMENT LINEARIZATION CONTROL SYSTEM." Cybernetics and Systems 31, no. 1 (2000): 115–35. http://dx.doi.org/10.1080/019697200124946.

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Brzózka, Jerzy. "Design and Analysis of Model Following Control Structure with Nonlinear Plant." Solid State Phenomena 180 (November 2011): 3–10. http://dx.doi.org/10.4028/www.scientific.net/ssp.180.3.

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Abstract. Linearization methods of the object: input-state and input-output linearization are used usually in a standard feedback control system. However, these systems are sensitive to the changes of nonlinear characteristics of the plant. These changes can be compensated in two types of control systems: in the model following control (MFC) and adaptive. The article presents the first solution and contains: miscellaneous structures of linear control systems with model following, brief description of the linearization’s methods, simulation example of the course control of vessel and the advant

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Li, Chunbiao, Julien Clinton Sprott, and Wesley Thio. "Linearization of the Lorenz system." Physics Letters A 379, no. 10-11 (2015): 888–93. http://dx.doi.org/10.1016/j.physleta.2015.01.003.

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Lenz, Henning, and Dragan Obradovic. "Robust Control of the Chaotic Lorenz System." International Journal of Bifurcation and Chaos 07, no. 12 (1997): 2847–54. http://dx.doi.org/10.1142/s0218127497001928.

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This paper presents a global approach for controlling the Lorenz system. The basic idea is to partially cancel the nonlinear cross-coupling terms such that the stability of the resulting system can be guaranteed by sequentially proving the stability of each individual state. The method combines ideas from feedback linearization, classical control theory, and Lyapunov's second method. Robust behavior with respect to model uncertainties in the feedback loop is proven. The performance of partial linearization compared to input-state linearization is illustrated on tracking of several trajectories

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Zhang, Bin, and Yung C. Shin. "A Data-Driven Approach of Takagi-Sugeno Fuzzy Control of Unknown Nonlinear Systems." Applied Sciences 11, no. 1 (2020): 62. http://dx.doi.org/10.3390/app11010062.

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A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input–output data to approximate the nonlinear systems for which analytical mathematical models are not available. Then, the T-S fuzzy models are derived from the direct linearization of the neuro-fuzzy models. The operating points for linearization are chosen using the evolutionary strategy to minimize the global approximation error so that the T-S fuzzy

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Cover, Alan, James Reneke, Suzanne Lenhart, and Vladimir Protopopescu. "RKH Space Methods for Low Level Monitoring and Control of Nonlinear Systems II. A Vector-Case Example: The Lorenz System." Mathematical Models and Methods in Applied Sciences 07, no. 06 (1997): 823–45. http://dx.doi.org/10.1142/s0218202597000426.

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By using techniques from the theory of reproducing kernel Hilbert (RKH) spaces, we continue the exploration of the stochastic linearization method for possibly unknown and/or noise corrupted nonlinear systems. The aim of this paper is twofold: (a) the stochastic linearization formalism is explicitly extended to the vector case; and (b) as an illustration, the performance of the stochastic linearization for monitoring and control is assessed in the case of the Lorenz system for which the dynamic behavior is known independently.

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Chang, R. J., and S. J. Lin. "Statistical Linearization Model for the Response Prediction of Nonlinear Stochastic Systems Through Information Closure Method." Journal of Vibration and Acoustics 126, no. 3 (2004): 438–48. http://dx.doi.org/10.1115/1.1688762.

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A new linearization model with density response based on information closure scheme is proposed for the prediction of dynamic response of a stochastic nonlinear system. Firstly, both probability density function and maximum entropy of a nonlinear stochastic system are estimated under the available information about the moment response of the system. With the estimated entropy and property of entropy stability, a robust stability boundary of the nonlinear stochastic system is predicted. Next, for the prediction of response statistics, a statistical linearization model is constructed with the es

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9

Li, W., N. Bartzoudis, JR Fernandez, D. López-Bueno, G. Montoro, and P.L. Gilabert. "FPGA Implementation of a Linearization System for Wideband Envelope Tracking Power Amplifiers." IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 71, no. 4 (2023): 1781–92. https://doi.org/10.1109/TMTT.2022.3217842.

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This article focuses on the implementation of a linearization system for envelope tracking (ET) power amplifiers (PAs) in field-programmable gate array (FPGA). The ET PA linearization system includes a slew-rate reduction envelope generator, a RF leakage cancellation system in the supply envelope path and a baseband I-Q digital predistorter (DPD). This work targets the implementation of an ET PA linearization system on a radio frequency system-on-chip (RFSoC) device running under a demanding baseband sampling frequency of 614.4 MHz, which allows handling communication signals with up to 200 MH

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Wang, Dini, Fanwei Meng, and Shengya Meng. "Linearization Method of Nonlinear Magnetic Levitation System." Mathematical Problems in Engineering 2020 (June 22, 2020): 1–5. http://dx.doi.org/10.1155/2020/9873651.

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Linearized model of the system is often used in control design. It is generally believed that we can obtain the linearized model as long as the Taylor expansion method is used for the nonlinear model. This paper points out that the Taylor expansion method is only applicable to the linearization of the original nonlinear function. If the Taylor expansion is used for the derived nonlinear equation, wrong results are often obtained. Taking the linearization model of the maglev system as an example, it is shown that the linearization should be carried out with the process of equation derivation. T

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Dissertations / Theses on the topic "System Linearization"

1

Lee, Jungkun. "Optimal linearization of anharmonic oscillators /." Online version of thesis, 1991. http://hdl.handle.net/1850/11021.

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Liu, Yong. "NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159.

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Yang, Bo. "Output Feedback Control of Nonlinear Systems with Unstabilizable/Undetectable Linearization." Case Western Reserve University School of Graduate Studies / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=case1132634014.

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Maeda, Ken. "Nonlinear control system of inverted pendulum based on input-output linearization." Diss., Online access via UMI:, 2006.

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5

Han, JeongHeon. "An LMI approach to stochastic linear system design using alternating linearization /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3184209.

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Huang, Rui. "OUTPUT FEEDBACK TRACKING CONTROL OF NONLINEAR TIME-VARYING SYSTEMS BY TRAJECTORY LINEARIZATION." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1178906759.

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Eriksson, Marcus. "Analysis of Digital Predistortion in a Wideband Arbitrary Waveform Generator." Thesis, Linköpings universitet, Kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-123410.

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Digital predistortion is a signal processing technique used to remove undesired distortions caused by nonlinear system effects. This method is predominately used to linearize power amplifiers in communication systems in order to achieve efficient transmitter circuits. However, the technique can readily be applied to cancel undesired nonlinear behavior in other types of systems. This thesis investigates the effectiveness of digital predistortion in the context of a wideband arbitrary waveform generator. A theoretical foundation discussing nonlinear system models, predistortion architectures and

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Gettman, Chang-Ching Lo. "Multivariable control of the space shuttle remote manipulator system using linearization by state feedback." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/46419.

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Lindahl, Karl-Olof. "On the linearization of non-Archimedean holomorphic functions near an indifferent fixed point." Doctoral thesis, Växjö : Växjö University Press, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-1713.

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Rothman, Keith Eric. "Validation of Linearized Flight Models using Automated System-Identification." DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/81.

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Optimization based flight control design tools depend on automatic linearization tools, such as Simulink®’s LINMOD, to extract linear models. In order to ensure the usefulness and correctness of the generated linear model, this linearization must be accurate. So a method of independently verifying the linearized model is needed. This thesis covers the automation of a system identification tool, CIFER®, for use as a verification tool integrated with CONDUIT®, an optimization based design tool. Several test cases are built up to demonstrate the accuracy of the verification tool with respect

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Books on the topic "System Linearization"

1

United States. National Aeronautics and Space Administration., ed. Multivariable control of the space shuttle remote manipulator system using linearization by state feedback. National Aeronautics and Space Administration, 1993.

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2

Lee, Hong-Gi. Linearization of Nonlinear Control Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3643-2.

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Socha, Leslaw. Linearization Methods for Stochastic Dynamic Systems. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-72997-6.

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Shoikhet, David, and Mark Elin. Linearization Models for Complex Dynamical Systems. Birkhäuser Basel, 2010. http://dx.doi.org/10.1007/978-3-0346-0509-0.

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5

-H, Steeb W., ed. Nonlinear dynamical systems and Carleman linearization. World Scientific, 1991.

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6

G, Meyer, Su R, and Ames Research Center, eds. Approximating linearizations for nonlinear systems. National Aeronautics and Space Administration, Ames Research Center, 1986.

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7

Pshenichnyj, Boris N. The Linearization Method for Constrained Optimization. Springer Berlin Heidelberg, 1994.

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8

Minhas, Rajinderjeet Singh. Adaptive feedback linearization of systems with non-lipschitz nonlinearities. National Library of Canada, 1996.

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9

Dzielski, John Edward. A feedback linearization approach to spacecraft control using momentum exchange devices. The Charles Stark Draper Laboratory, 1988.

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10

R, Su, and United States. National Aeronautics and Space Administration, eds. Approximations of nonlinear systems having outputs. National Aeronautics and Space Administration, 1985.

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Book chapters on the topic "System Linearization"

1

Kolk, W. Richard, and Robert A. Lerman. "Linearization." In Nonlinear System Dynamics. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4684-6494-8_4.

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2

Chechurin, Leonid, and Sergej Chechurin. "Nonlinear System Oscillations: Harmonic Linearization Method." In Physical Fundamentals of Oscillations. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-75154-2_7.

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3

Härdin, Hanna M., and Jan H. van Schuppen. "System Reduction of Nonlinear Positive Systems by Linearization and Truncation." In Positive Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-34774-7_55.

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4

Bak, Stanley, Sergiy Bogomolov, Brandon Hencey, Niklas Kochdumper, Ethan Lew, and Kostiantyn Potomkin. "Reachability of Koopman Linearized Systems Using Random Fourier Feature Observables and Polynomial Zonotope Refinement." In Computer Aided Verification. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13185-1_24.

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AbstractKoopman operator linearization approximates nonlinear systems of differential equations with higher-dimensional linear systems. For formal verification using reachability analysis, this is an attractive conversion, as highly scalable methods exist to compute reachable sets for linear systems. However, two main challenges are present with this approach, both of which are addressed in this work. First, the approximation must be sufficiently accurate for the result to be meaningful, which is controlled by the choice of observable functions during Koopman operator linearization. By using r

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Xiros, Nikolaos I. "Electromechanical System Applications." In Feedback Linearization of Dynamical Systems with Modulated States for Harnessing Water Wave Power. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-031-02491-7_4.

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Pachare, Ashwini, and Archana Thosar. "Level Control of Quadruple Tank System with Feedback Linearization." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0336-5_38.

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7

Ozaki, Tohru. "The Local Linearization Filter with Application to Nonlinear System Identifications." In Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0854-6_10.

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Osypiuk, Rafał. "Indirect Linearization Concept through the Forward Model-Based Control System." In Robot Motion and Control 2011. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2343-9_15.

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Kremer, Gereon, Andrew Reynolds, Clark Barrett, and Cesare Tinelli. "Cooperating Techniques for Solving Nonlinear Real Arithmetic in the cvc5 SMT Solver (System Description)." In Automated Reasoning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10769-6_7.

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AbstractThe SMT solver solves quantifier-free nonlinear real arithmetic problems by combining the cylindrical algebraic coverings method with incremental linearization in an abstraction-refinement loop. The result is a complete algebraic decision procedure that leverages efficient heuristics for refining candidate models. Furthermore, it can be used with quantifiers, integer variables, and in combination with other theories. We describe the overall framework, individual solving techniques, and a number of implementation details. We demonstrate its effectiveness with an evaluation on the SMT-LI

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Bociu, Lorena, and Jean-Paul Zolésio. "Linearization of a Coupled System of Nonlinear Elasticity and Viscous Fluid." In Modern Aspects of the Theory of Partial Differential Equations. Springer Basel, 2011. http://dx.doi.org/10.1007/978-3-0348-0069-3_6.

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Conference papers on the topic "System Linearization"

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Pintea, Paul, Vlad Mihaly, Mircea Şuşcă, and Petru Dobra. "Koopman Linearization and Optimal Control of Glucose Level." In 2024 28th International Conference on System Theory, Control and Computing (ICSTCC). IEEE, 2024. http://dx.doi.org/10.1109/icstcc62912.2024.10744740.

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Manjhi, Ashish, Umberto Saetti, and Joseph Horn. "Analytical Linearization of a State-Space Free Vortex Wake Model." In Vertical Flight Society 80th Annual Forum & Technology Display. The Vertical Flight Society, 2024. http://dx.doi.org/10.4050/f-0080-2024-1254.

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This paper presents the development and application of analytical linearization of a State-Space Free Vortex Wake Model. Previous work developed a state-space free wake model that could be numerically linearized via finite differences into a Linear Time Periodic (LTP) system, but the numerical linearization process was computationally expensive. An improved method is developed that uses exact analytical linearization of the Biot-Savart Law. The analytical method is found to speed up linearization computations by O(N), where N is the number of free wake nodes. A simple decoupled wake model is u

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3

Silva, M. P. S., A. A. Mello, F. G. Pinal, L. S. Ribeiro, J. S. Lima, and M. Silveira. "Adaptive linearization digital signals: I and Q [HDTV system PA linearization applications]." In IEEE Antennas and Propagation Society Symposium, 2004. IEEE, 2004. http://dx.doi.org/10.1109/aps.2004.1330490.

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Teodorescu, Horia-Nicolai L. "Fuzzy logic system linearization for sensors." In 2017 International Symposium on Signals, Circuits and Systems (ISSCS). IEEE, 2017. http://dx.doi.org/10.1109/isscs.2017.8034892.

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Lyu, Yibo, Xu Li, Weiwei Zhang, and Tianxiang Wang. "Digital Linearization for WDM-RoF System." In 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). IEEE, 2021. http://dx.doi.org/10.1109/vtc2021-spring51267.2021.9448651.

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Trenev, Ivan Sergeevich, and Daniil Dmitrievich Devyatkin. "Feedback Linearization Control of Nonlinear System." In INTELS’22. MDPI, 2023. http://dx.doi.org/10.3390/engproc2023033036.

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He, Tao, and Gabor C. Temes. "System-level noise filtering and linearization." In 2018 IEEE Custom Integrated Circuits Conference (CICC). IEEE, 2018. http://dx.doi.org/10.1109/cicc.2018.8357015.

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Gudkova, Natalya V., Vladimir M. Chuykov, and Ksenya V. Besklubova. "Digital adaptive system of power amplifier linearization." In 2015 IEEE East-West Design & Test Symposium (EWDTS). IEEE, 2015. http://dx.doi.org/10.1109/ewdts.2015.7493100.

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Michaelsen, Jorgen Andreas, and Dag T. Wisland. "A VCO linearization system for ADC applications." In 2013 IEEE 11th International New Circuits and Systems Conference (NEWCAS). IEEE, 2013. http://dx.doi.org/10.1109/newcas.2013.6573623.

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"Feedback linearization application for LLRF control system." In Proceedings of the 1999 American Control Conference. IEEE, 1999. http://dx.doi.org/10.1109/acc.1999.786288.

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Reports on the topic "System Linearization"

1

Kokotovic, Peter V. Nonlinear System Design: Adaptive Feedback Linearization with Unmodeled Dynamics. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada248484.

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Kokotovic, Petar V. Nonlinear System Design: Adaptive Feedback Linearization with Unmodeled Dynamics. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada261360.

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Jonkman, Jason, Alan D. Wright, Gregory Hayman, and Amy N. Robertson. Full-System Linearization for Floating Offshore Wind Turbines in OpenFAST: Preprint. Office of Scientific and Technical Information (OSTI), 2018. http://dx.doi.org/10.2172/1489323.

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คุณพนิชกิจ, ชัยโรจน์, та วิบูลย์ แสงวีระพันธุ์ศิริ. การควบคุมแบบย้อนกลับของหุ่นยนต์อุตสาหกรรมชนิดสามแกนหมุน. จุฬาลงกรณ์มหาวิทยาลัย, 1988. https://doi.org/10.58837/chula.res.1988.23.

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การควบคุมตำแหน่งของปลายแขนหุ่นยนต์อุตสาหกรรมเป็นหัวใจของการออกแบบระบบควบคุมทั้งหมด โดยจะพิจารณาการเคลื่อนที่ที่ปลายแขนในลักษณะจุดต่อจุดหรอ Point-to-Point เป็นหลัก ระบบควบคุมแบบย้อนกลับหรือแบบปิดที่จะนำมาควบคุมการเคลื่อนที่ที่ปลายแขนของหุ่นยนต์อุตสาหกรรมจะเป็นระบบควบคุมชนิด พี ไอ ดี (PID, Proportional-Integral-Derivative) การออกแบบระบบควบคุมนี้จะอาศัยแบบจำลองทางคณิตศาสตร์ของแขนหุ่นยนต์อุตสาหกรรมที่ได้ทำการปรับให้เป็นเชิงเส้นแล้ว (Linearization) และการเคลื่อนที่ที่ของแต่ละจ้อต่อก็อิสระไม่มีผลต่อกัน (Decoupling) ภายใต้เงื่อนไขที่ว่าความเร็วในการเคลื่อที่ของแต่ละข้อต่อของแขนหุ่นยนต์อุตสาหรรมนั้นไม

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5

Kim, Taihyun, and Eyad H. Abed. Stationary Bifurcation Control for Systems with Uncontrollable Linearization. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada438515.

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Wang, Jianliang, and Wilson J. Rugh. On the Pseudo-Linearization Problem for Nonlinear Systems. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada194021.

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