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E-raamat: Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities

(Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China), (University of Shanghai for Science and Technology, China), (Brunel University London, UK)
  • Formaat: 267 pages
  • Ilmumisaeg: 11-Oct-2018
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9780429880032
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Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced ComplexitiesSuurem pilt
  • Formaat: 267 pages
  • Ilmumisaeg: 11-Oct-2018
  • Kirjastus: CRC Press
  • Keel: eng
  • ISBN-13: 9780429880032
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The book addresses the system performance with a focus on the network-enhanced complexities and developing the engineering-oriented design framework of controllers and filters with potential applications in system sciences, control engineering and signal processing areas. Therefore, it provides a unified treatment on the analysis and synthesis for discrete-time stochastic systems with guarantee of certain performances against network-enhanced complexities with applications in sensor networks and mobile robotics. Such a result will be of great importance in the development of novel control and filtering theories including industrial impact.

Key Features











Provides original methodologies and emerging concepts to deal with latest issues in the control and filtering with an emphasis on a variety of network-enhanced complexities





Gives results of stochastic control and filtering distributed control and filtering, and security control of complex networked systems





Captures the essence of performance analysis and synthesis for stochastic control and filtering





Concepts and performance indexes proposed reflect the requirements of engineering practice





Methodologies developed in this book include backward recursive Riccati difference equation approach and the discrete-time version of input-to-state stability in probability
Preface xi
Acknowledgements xv
Symbols xvii
1 Introduction
1(18)
1.1 Discrete-Time Stochastic Systems
1(3)
1.2 Network-Enhanced Complexities
4(3)
1.3 Performance Analysis and Engineering Design Synthesis
7(5)
1.4 Outline
12(7)
2 Finite-Horizon H∞ Control with Randomly Occurring Nonlinearities and Fading Measurements
19(18)
2.1 Modeling and Problem Formulation
20(2)
2.2 H∞ Performance Analysis
22(8)
2.3 H∞ Controller Design
30(2)
2.4 Simulation Examples
32(2)
2.5 Summary
34(3)
3 Finite-Horizon H∞ Consensus Control for Multi-Agent Systems with Missing Measurements
37(22)
3.1 Modeling and Problem Formulation
38(3)
3.2 Consensus Performance Analysis
41(6)
3.3 Hoc Controller Design
47(4)
3.4 Simulation Examples
51(1)
3.5 Summary
52(7)
4 Finite-Horizon Distributed H∞ State Estimation with Stochastic Parameters through Sensor Networks
59(22)
4.1 Modeling and Problem Formulation
60(3)
4.2 Hoc Performance Analysis
63(6)
4.3 Distributed Filter Design
69(6)
4.4 Simulation Examples
75(2)
4.5 Summary
77(4)
5 Finite-Horizon Dissipative Control for State-Saturated Discrete Time-Varying Systems with Missing Measurements
81(22)
5.1 Modeling and Problem Formulation
81(3)
5.2 Dissipative Control for Full State Saturation Case
84(10)
5.3 Dissipative Control for Partial State Saturation Case
94(4)
5.4 Simulation Examples
98(1)
5.5 Summary
99(4)
6 Finite-Horizon H∞ Filtering for State-Saturated Discrete Time-Varying Systems with Packet Dropouts
103(20)
6.1 Modeling and Problem Formulation
103(3)
6.2 H∞ Filtering for Full State Saturation Case
106(6)
6.3 H∞ Filtering for Partial State Saturation Case
112(4)
6.4 Simulation Examples
116(2)
6.5 Summary
118(5)
7 Finite-Horizon Envelope-Constrained H∞ Filtering with Fading Measurements
123(20)
7.1 Modeling and Problem Formulation
124(3)
7.2 H∞ Performance Analysis
127(4)
7.3 Envelope Constraint Analysis
131(5)
7.4 Envelope-Constrained H∞ Filter Design
136(2)
7.5 Simulation Examples
138(2)
7.6 Summary
140(3)
8 Distributed Filtering under Uniform Quantizations and Deception Attacks through Sensor Networks
143(20)
8.1 Modeling and Problem Formulation
144(2)
8.2 Distributed Filter Design
146(8)
8.3 Boundedness Analysis
154(5)
8.4 Simulation Examples
159(1)
8.5 Summary
160(3)
9 Event-Triggered Distributed H∞ State Estimation with Packet Dropouts through Sensor Networks
163(16)
9.1 Modeling and Problem Formulation
164(3)
9.2 H∞ Performance Analysis
167(4)
9.3 H∞ Estimator Design
171(2)
9.4 Simulation Examples
173(2)
9.5 Summary
175(4)
10 Event-Triggered Consensus Control for Multi-Agent Systems in the Framework of Input-to-State Stability in Probability
179(22)
10.1 Modeling and Problem Formulation
180(3)
10.2 Analysis of Input-to-State Stability in Probability
183(5)
10.3 Event-Triggered Consensus Control for Multi-Agent Systems
188(7)
10.4 Simulation Examples
195(2)
10.5 Summary
197(4)
11 Event-Triggered Security Control for Discrete-Time Stochastic Systems Subject to Cyber-Attacks
201(14)
11.1 Problem Formulation
202(3)
11.2 Security Performance Analysis
205(3)
11.3 Security Controller Design
208(4)
11.4 Simulation Examples
212(2)
11.5 Summary
214(1)
12 Event-Triggered Consensus Control for Multi-Agent Systems Subject to Cyber-Attacks in the Framework of Observers
215(20)
12.1 Modeling and Problem Formulation
216(6)
12.2 Consensus Analysis
222(4)
12.3 Consensus Controller Design
226(3)
12.4 Simulation Examples
229(2)
12.5 Summary
231(4)
Bibliography 235(14)
Index 249
Derui Ding, Zidong Wang, Guoliang Wei
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
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