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E-raamat: Adaptive Regulation: Reference Tracking and Disturbance Rejection

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Adaptive Regulation: Reference Tracking and Disturbance RejectionSuurem pilt
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This monograph is focused on control law design methods for asymptotic tracking and disturbance rejection in the presence of uncertainties. The methods are based on adaptive implementation of the Internal Model Principle (IMP). The monograph shows how this principle can be applied to the problems of asymptotic rejection/tracking of a priori uncertain exogenous signals for linear and nonlinear plants with known and unknown parameters. 





The book begins by introducing the problems of adaptive control, the challenges that are faced, modern methods and an overview of the IMP. It then introduces special observers for uncertain exogeneous signals affecting linear and nonlinear systems with known and unknown parameters. The basic algorithms of adaptation applied to the canonical closed-loop error models are presented. The authors then address the systematic design of adaptive systems for asymptotic rejection/tracking of a priori uncertain exosignals. The monograph also discusses the adaptive rejection/tracking of a priori uncertain exogenous signals in systems with input delay, the problems of performance improvement in disturbance rejection and reference tracking and the issue of robustness of closed-loop systems. 





Adaptive Regulation provides a systematic discussion of the IMP applied to a variety of control problems, making it of interest to researchers and industrial practitioners.
1 Introduction and Problem Statement
1(42)
1.1 Adaptation Against Uncertainties
1(6)
1.2 Challenges of Signal Uncertainties
7(10)
1.3 Output Regulation
17(11)
1.3.1 Nonadaptive Output Regulation: Problem Statement and the Francis Equation
17(4)
1.3.2 Decomposition on Tracking and Rejection
21(4)
1.3.3 Adaptive Output Regulation: Statements of the Problems
25(3)
1.4 Internal Model and Output Regulation: An Overview
28(3)
1.5 Internal Model and Output Regulation: Practical Implementations
31(5)
1.5.1 Vibration Control
31(1)
1.5.2 Ripple Reduction in AC-DC Converters
32(2)
1.5.3 Ripple Reduction in Permanent Magnet Synchronous Motors
34(1)
1.5.4 Crane Vessel Control
35(1)
References
36(7)
2 Exosignals: Models and Observers
43(52)
2.1 Exosignal Models
43(6)
2.2 Exosystem Canonical Form
49(8)
2.3 Reference Observer
57(1)
2.4 Disturbance Observers: Plants with Known Parameters
58(18)
2.4.1 Disturbance Observers for LTI Plants
58(10)
2.4.2 Disturbance Observers for Nonlinear Plants
68(8)
2.5 Disturbance Observers: Plants with Unknown Parameters
76(17)
2.5.1 Disturbance Observers for LTI Plants
76(9)
2.5.2 Disturbance Observers for Nonlinear Plants
85(8)
References
93(2)
3 Basic Algorithms of Adaptation
95(44)
3.1 Parameterizations and Error Models
95(4)
3.2 Algorithms for Static Error Model
99(15)
3.2.1 Gradient Algorithm of Adaptation
100(4)
3.2.2 Adaptation Algorithm with Dynamic Regressor Extension
104(3)
3.2.3 Adaptation Algorithm with Memory Regressor Extension
107(7)
3.3 Algorithms for Dynamic Error Model with Accessible State
114(9)
3.3.1 Adaptive Stabilization
116(3)
3.3.2 Nonlinear Damping
119(4)
3.4 Algorithms for Dynamic Error Model with Accessible Output
123(7)
3.4.1 Adaptive Output Stabilization of Strictly Passive Systems
124(2)
3.4.2 Swapping-Based Adaptation
126(4)
3.5 Robust Algorithms of Adaptation
130(7)
References
137(2)
4 Adaptive Regulation in Systems with Known Parameters
139(84)
4.1 LTI SISO Plants
139(42)
4.1.1 Reference Tracking
139(15)
4.1.2 Compensation of Matched Disturbance
154(3)
4.1.3 Compensation of Unmatched Disturbance
157(19)
4.1.4 Regulation in LTI SISO Plants
176(5)
4.2 LTI MIMO Plants
181(18)
4.2.1 Reference Tracking
182(10)
4.2.2 Compensation of Unmatched Disturbance
192(3)
4.2.3 Regulation in LTI MIMO Plants
195(4)
4.3 Disturbance Compensation in Nonlinear Plants
199(21)
4.3.1 Plant in the General Form
201(3)
4.3.2 Plant in the Normal Canonical Form
204(4)
4.3.3 Plant with Unmatched Disturbance and Measured State
208(6)
4.3.4 Plant with Unmatched Disturbance and Measured Output
214(6)
References
220(3)
5 Adaptive Regulation in Systems with Unknown Parameters
223(44)
5.1 LTI SISO Plants
223(21)
5.1.1 Reference Tracking
223(4)
5.1.2 Compensation of Matched Disturbance
227(4)
5.1.3 Compensation of Unmatched Disturbance
231(11)
5.1.4 Regulation in LTI SISO Plants
242(2)
5.2 Nonlinear Plants
244(20)
5.2.1 Reference Tracking
245(6)
5.2.2 Compensation of Unmatched Disturbance
251(13)
References
264(3)
6 Adaptive Regulation in LTI Plants with Input Delay
267(22)
6.1 Reference Tracking
267(7)
6.2 Disturbance Compensation
274(7)
6.3 Regulation
281(6)
References
287(2)
7 Robust Adaptive Regulation
289(22)
7.1 Robustness of Exosignal Observers
289(7)
7.1.1 Reference Observer
290(1)
7.1.2 Disturbance Observers: Plants with Known Parameters
291(1)
7.1.3 Disturbance Observers: Plants with Unknown Parameters
292(4)
7.2 Reference Tracking
296(5)
7.3 Disturbance Rejection
301(7)
7.3.1 LTI SISO Plants with Known Parameters
301(3)
7.3.2 LTI SISO Plants with Unknown Parameters
304(2)
7.3.3 Nonlinear Plant with Unmatched Disturbance and Measured State
306(2)
7.4 Output Regulation
308(2)
References
310(1)
Appendix A Exosignals: Parameterizations and Properties 311(10)
Appendix B Stability, Lyapunov Functions and Robustness 321(10)
Appendix C Norms and Properties of Functions 331(2)
Appendix D Schemes of Swapping 333(12)
Appendix E Adaptive Backstepping 345(10)
Index 355
Vladimir O. Nikiforov received his Electrical Engineering Degree, PhD and Doctor of Science degrees from what is currently known as Saint-Petersburg University of Information Technologies, Mechanics and Optics (ITMO University), in 1986, 1991 and 2001 respectively. Since 1986, Nikiforov has been working in different positions at ITMO University, and since 2001 he has been a Professor in the Faculty of Control Systems and Robotics. He has also worked part time as a senior researcher at other institutions. From 2003 to 2008 V. Nikiforov acted as Associate Editor of Automatica IFAC Journal and he is currently Editor-in-Chief of the journals Control Engineering Russia and Scientific and Technical Journal of Information Technologies, Mechanics and Optics. He has authored or co-authored more than 150 titles, including 5 monographs and 3 textbooks. His research interests are primarily within adaptive and nonlinear control of complex systems, trajectory control of linear and nonlinear systems and adaptive regulation and servomechanism problems.





Dmitry N. Gerasimov gained his electrical engineering degree and PhD from ITMO University in 2005 and 2009 respectively. Since 2009, Dmitry Gerasimov has been with the Department of Control Systems and Informatics at ITMO University and, currently, he holds a position of associate professor of the Faculty of Control Systems and Industrial Robotics. His research interests are in adaptive and robust control, nonlinear control, delayed systems, automation systems and industrial controllers, and spark ignition and diesel engine modelling and control. He has authored or co-authored more than 50 titles. 
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