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Estimation and Control for Networked Systems with Packet Losses without Acknowledgement 1st ed. 2017 [Hardback]

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  • Formāts: Hardback, 188 pages, height x width: 235x155 mm, weight: 4321 g, 27 Illustrations, color; 12 Illustrations, black and white; XIII, 188 p. 39 illus., 27 illus. in color., 1 Hardback
  • Sērija : Studies in Systems, Decision and Control 77
  • Izdošanas datums: 30-Sep-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319442112
  • ISBN-13: 9783319442112
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Estimation and Control for Networked Systems with Packet Losses without Acknowledgement 1st ed. 2017Palielināt
  • Formāts: Hardback, 188 pages, height x width: 235x155 mm, weight: 4321 g, 27 Illustrations, color; 12 Illustrations, black and white; XIII, 188 p. 39 illus., 27 illus. in color., 1 Hardback
  • Sērija : Studies in Systems, Decision and Control 77
  • Izdošanas datums: 30-Sep-2016
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3319442112
  • ISBN-13: 9783319442112
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783319442112.html
Keywords:
This book discusses recent advances in the estimation and control of networked systems with unacknowledged packet losses: systems usually known as user-datagram-protocol-like. It presents both the optimal and sub-optimal solutions in the form of algorithms, which are designed to be implemented easily by computer routines. It also provides MATLAB® routines for the key algorithms. It shows how these methods and algorithms can solve estimation and control problems effectively, and identifies potential research directions and ideas to help readers grasp the field more easily.The novel auxiliary estimator method, which is able to deal with estimators that consist of exponentially increasing terms, is developed to analyze the stability and convergence of the optimal estimator. The book also explores the structure and solvability of the optimal control, i.e. linear quadratic Gaussian control. It develops various sub-optimal but efficient solutions for estimation and control for industr

ial and practical applications, and analyzes their stability and performance.This is a valuable resource for researchers studying networked control systems, especially those related to non-TCP-like networks. The practicality of the ideas included makes it useful for engineers working with networked control.

Introduction.- Optimal Estimation and Control for UDP-Like Systems.- An Auxiliary Estimator Method.- Stability and Convergence of optimal Estimator for UDP-Like Systems.- Auxiliary-Estimator-Based Suboptimal Estimators for UDP-Like Systems.
1 Introduction
1(16)
1.1 Networked Control Systems
1(3)
1.2 Literature Review
4(2)
1.3 Book Organization
6(11)
Appendix
7(5)
References
12(5)
2 Optimal Estimation and Control for UDP-Like Systems
17(20)
2.1 Introduction
17(1)
2.2 System Setup and Problem Formulation
17(2)
2.2.1 System Setup
17(1)
2.2.2 Problem Formulation
18(1)
2.3 Optimal Estimator
19(6)
2.3.1 Probability Density Function of System States
20(2)
2.3.2 Optimal Estimator
22(1)
2.3.3 Optimal Estimator Under Some Special Conditions
23(2)
2.4 Optimal Control
25(5)
2.4.1 Optimal Control Under Some Special Conditions
28(2)
2.5 Numerical Example
30(2)
2.6 Conclusions and Further Researches
32(5)
Appendix
33(3)
References
36(1)
3 An Auxiliary Estimator Method
37(22)
3.1 Introduction
37(1)
3.2 System Setup and Problem Formulation
37(1)
3.3 The Auxiliary Estimator Method
38(10)
3.3.1 Construction of Auxiliary System States
39(2)
3.3.2 Probability Density Functions of Auxiliary System States
41(2)
3.3.3 Estimation of Auxiliary System States
43(1)
3.3.4 Relationship Between the Optimal and Auxiliary Estimators
44(4)
3.4 Numerical Example
48(1)
3.5 Conclusions and Further Researches
49(10)
Appendix
51(7)
References
58(1)
4 Stability of Optimal Estimator for UDP-Like Systems
59(16)
4.1 Introduction
59(1)
4.2 System Setup and Problem Formulation
59(1)
4.3 Stability of the Optimal Estimator
60(8)
4.3.1 The Bounded Input Case
60(2)
4.3.2 The Unbounded Input Case
62(6)
4.4 Numerical Example
68(3)
4.5 Conclusions and Further Researches
71(4)
Appendix
73(1)
References
74(1)
5 Auxiliary-Estimator-Based Suboptimal Estimators for UDP-Like Systems
75(14)
5.1 Introduction
75(1)
5.2 System Setup
75(1)
5.3 Fast Filtering Algorithm 1
76(5)
5.3.1 Construction of Auxiliary Estimator
76(3)
5.3.2 Fast Filtering Algorithm
79(1)
5.3.3 Stability of FF1
80(1)
5.4 Fast Filtering Algorithm 2
81(2)
5.4.1 Stability of FF2
82(1)
5.5 Numerical Example
83(3)
5.6 Conclusions and Further Researches
86(3)
References
87(2)
6 Linear Quadratic Gaussian Control for UDP-Like Systems
89(24)
6.1 Introduction
89(1)
6.2 System Setup and Problem Formulation
89(4)
6.2.1 System Setup
89(1)
6.2.2 Framework for the LQG Problem
90(2)
6.2.3 Problem Formulation
92(1)
6.3 Fast Filter
93(4)
6.3.1 Fast Filter
93(1)
6.3.2 Properties of the Fast Filter
94(3)
6.4 Main Results
97(7)
6.4.1 Finite Horizon LQG Control
97(2)
6.4.2 Infinite Horizon LQG Control
99(5)
6.5 Numerical Examples
104(2)
6.6 Conclusions and Further Researches
106(7)
Appendix
108(1)
References
109(4)
7 Merging-Technique-Based Suboptimal Estimator for Quasi-TCP-Like Systems
113(20)
7.1 Introduction
113(1)
7.2 System Setup and Problem Formulation
113(3)
7.2.1 Systems Setup
113(2)
7.2.2 The Impact of the Losses of ACKs on Estimation
115(1)
7.3 Fast Filtering Algorithm
116(3)
7.3.1 Framework of Fast Filtering Algorithm
116(1)
7.3.2 Fast Filtering Algorithm
116(2)
7.3.3 Recursive Formulas for Fast Filtering Algorithm
118(1)
7.4 Stability of Fast Filter
119(2)
7.5 Numerical Examples
121(4)
7.6 Conclusions and Further Researches
125(8)
Appendix
126(5)
References
131(2)
8 Estimation and Control for Quasi-TCP-Like Systems
133(28)
8.1 Introduction
133(1)
8.2 System Setup and Problem Formulation
134(2)
8.2.1 System Setup
134(1)
8.2.2 Problems Formulation
135(1)
8.3 Optimal Estimator
136(3)
8.3.1 Probability Density Function of System States
137(1)
8.3.2 Optimal Estimator for the Quasi-TCP-Like System
138(1)
8.4 Solvability of the Optimal LQG Problem
139(3)
8.5 Suboptimal LQG Control
142(5)
8.5.1 Suboptimal Linear Estimator
143(1)
8.5.2 Suboptimal LQG Controller
144(3)
8.5.3 Stability of the Closed-Loop Systems
147(1)
8.6 Numerical Examples
147(4)
8.7 Conclusions and Further Researches
151(10)
Appendix
152(7)
References
159(2)
9 Matlab Routines
161(26)
9.1 Routines in Chap. 2
161(7)
9.1.1 Main Routines
161(1)
9.1.2 Subroutines
162(6)
9.2 Routines in Chap. 3
168(3)
9.2.1 Main Routines
168(1)
9.2.2 Subroutines
169(2)
9.3 Routines in Chap. 4
171(3)
9.3.1 Main Routines
171(3)
9.3.2 Subroutines
174(1)
9.4 Routines in Chap. 5
174(5)
9.4.1 Main Routines
174(3)
9.4.2 Subroutines
177(2)
9.5 Routines in Chap. 6
179(3)
9.6 Routines in Chap. 7
182(2)
9.7 Routines in Chap. 8
184(3)
Index 187
Hong Lin as been awarded the status first of Excellent Student in Zhejiang University and then of Excellent Educator in Concord College Fujian Normal University. He is an active reviewer for many international journals.





Hongye Su is the author of 100 journal papers and 8 books. He has undertaken more than ten national funds and state key projects as the principal investigator, including National Outstanding Youth Science Foundation of China, National Natural Science Foundation of China, Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE, PRC, and projects for National High Technology Research and Development Program of China (863 Program), etc.





Peng Shi has actively served in the editorial board of a number of journals, including Automatica, IEEE Transactions on Automatic Control; IEEE Transactions on Fuzzy Systems. He is a Fellow of the Institution of Engineering and Technology, and the Institute of Mathematics and its Applications. He was the Chair of Control Aerospace and Electronic Systems Chapter, IEEE South Australia Section; and now he is Member of College of Expert, Australian Research Council. He serves as an IEEE Systems, Man and Cybernetics Society Distinguished Lecturer for 2016-2017.





Zhan Shu is an Associate Editor for the Journal of The Franklin Institute, Asian Journal of Control, and Mathematical Problems in Engineering. He is a member in the editorial board of the Open Automation and Control Systems Journal and IEEE Control Systems Society Conference.





Zheng-Guang Wu currently serves as an Associate Editor for IEEE Access and an Editorial Board Member for Neurocomputing. He is a very active reviewer for many international journals.