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El. knyga: Spacecraft Attitude Control: A Linear Matrix Inequality Approach

(Professor, Northwestern Technical University, China), (Research Assistant, Harbin Institute of Technology, China), (Associate Professor, Northwestern Polytechnical University, China), (Professor, Harbin Institute of Technology, China)
  • Formatas: PDF+DRM
  • Išleidimo metai: 31-Jan-2022
  • Leidėjas: Elsevier - Health Sciences Division
  • Kalba: eng
  • ISBN-13: 9780323990066
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Spacecraft Attitude Control: A Linear Matrix Inequality ApproachDidesnis paveikslėlis
  • Formatas: PDF+DRM
  • Išleidimo metai: 31-Jan-2022
  • Leidėjas: Elsevier - Health Sciences Division
  • Kalba: eng
  • ISBN-13: 9780323990066
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Spacecraft Attitude Control: A Linear Matrix Inequality Approach solves problems for spacecraft attitude control systems using convex optimization and, specifi cally, through a linear matrix inequality (LMI) approach. High-precision pointing and improved robustness in the face of external disturbances and other uncertainties are requirements for the current generation of spacecraft. This book presents an LMI approach to spacecraft attitude control and shows that all uncertainties in the maneuvering process can be solved numerically. It explains how a model-like state space can be developed through a mathematical presentation of attitude control systems, allowing the controller in question to be applied universally. The authors describe a wide variety of novel and robust controllers, applicable both to spacecraft attitude control and easily extendable to second-order systems. Spacecraft Attitude Control provides its readers with an accessible introduction to spacecraft attitude control and robust systems, giving an extensive survey of current research and helping researchers improve robust control performance.

  • Considers the control requirements of modern spacecraft
  • Presents rigid and flexible spacecraft control systems with inherent uncertainties mathematically, leading to a model-like state space
  • Develops a variety of novel and robust controllers directly applicable to spacecraft control as well as extendable to other second-order systems
  • Includes a systematic survey of recent research in spacecraft attitude control
Preface xi
1 Introduction of basic knowledge
1(36)
1.1 Linear matrix inequalities
1(20)
1.1.1 What are linear matrix inequalities?
1(7)
1.1.2 Useful lemmas for linear matrix inequalities
8(6)
1.1.3 Advantages of linear matrix inequalities
14(1)
1.1.4 Some standard linear matrix inequalitie problems
15(6)
1.2 Spacecraft attitude kinematics and dynamics
21(16)
1.2.1 Attitude representations
22(6)
1.2.2 Attitude kinematics
28(3)
1.2.3 Attitude dynamics
31(3)
References
34(3)
2 State feedback nonfragile control
37(26)
2.1 Introduction
37(1)
2.2 Problem formulation
38(5)
2.2.1 Attitude dynamics modeling
38(4)
2.2.2 Control objective
42(1)
2.3 State feedback nonfragile control law
43(7)
2.3.1 Some lemmas
43(1)
2.3.2 Sufficient conditions under additive perturbation
44(4)
2.3.3 Sufficient conditions under multiplicative perturbation
48(2)
2.4 Simulation test
50(9)
2.4.1 Simulation results under additive perturbation
51(2)
2.4.2 Simulation results under multiplicative perturbation
53(2)
2.4.3 Simulation results using a mixed H2/Hm controller
55(4)
2.5 Conclusions
59(4)
References
60(3)
3 Dynamic output feedback nonfragile-control
63(44)
3.1 Introduction
63(2)
3.2 Problem formulation
65(6)
3.2.1 Attitude system description
65(3)
3.2.2 Nonfragile control problem
68(2)
3.2.3 Control objective
70(1)
3.3 Dynamic output feedback nonfragile control law design
71(16)
3.3.1 Some lemmas
71(5)
3.3.2 Controller design under additive perturbation
76(3)
3.3.3 Controller design under multiplicative perturbation
79(2)
3.3.4 Controller design under coexisting additive and multiplicative perturbations
81(6)
3.4 Simulation test
87(18)
3.4.1 Simulation results under additive perturbation
87(6)
3.4.2 Simulation results under multiplicative perturbation
93(9)
3.4.3 Simulation results under coexisting additive and multiplicative perturbations
102(3)
3.5 Conclusions
105(2)
References
105(2)
4 Observer-based fault tolerant delayed control
107(32)
4.1 Introduction
107(3)
4.2 Problem formulation
110(3)
4.2.1 Attitude system description
110(3)
4.2.2 Control objective
113(1)
4.3 Observer-based fault tolerant control scheme
113(14)
4.3.1 Intermediate observer design
113(1)
4.3.2 Delayed controller design
114(1)
4.3.3 Control solution
115(12)
4.4 Simulation test
127(9)
4.4.1 Simulation results using the proposed controller
128(4)
4.4.2 Simulation results using the prediction-based sampled-data Hx controller
132(2)
4.4.3 Comparison analysis using different controllers
134(2)
4.5 Conclusions
136(3)
References
136(3)
5 Observer-based fault tolerant nonfragile control
139(38)
5.1 Introduction
139(3)
5.2 Problem formulation
142(6)
5.2.1 Attitude system description
142(4)
5.2.2 Stochastically intermediate observer design
146(1)
5.2.3 Nonfragile controller design
147(1)
5.2.4 Control objective
148(1)
5.3 Feasible solution for both cases
148(8)
5.3.1 Some lemmas
148(1)
5.3.2 Sufficient conditions under additive perturbation
149(3)
5.3.3 Sufficient conditions under multiplicative perturbation
152(4)
5.4 Simulation test
156(17)
5.4.1 Comparison analysis under additive perturbation
158(8)
5.4.2 Comparison analysis under multiplicative perturbation
166(7)
5.5 Conclusions
173(4)
References
173(4)
6 Disturbance observer-based control with input MRCs
177(28)
6.1 Introduction
177(3)
6.2 Problem formulation
180(2)
6.2.1 Attitude system description
180(2)
6.2.2 Control objective
182(1)
6.3 Controller design and analysis
182(9)
6.3.1 Some lemmas
183(1)
6.3.2 Coexisting conditions for observer and controller gains
184(1)
6.3.3 Proof and analysis
185(6)
6.4 Simulation test
191(11)
6.4.1 Nonzero angular rates
192(3)
6.4.2 Zero angular rates
195(2)
6.4.3 Evaluation indices for the three conditions
197(3)
6.4.4 Parametric influence on control performance
200(2)
6.5 Conclusions
202(3)
References
203(2)
7 Improved mixed control with poles assignment constraint
205(28)
7.1 Introduction
205(3)
7.2 Problem formulation
208(3)
7.2.1 Flexible spacecraft dynamics with two bending modes
208(1)
7.2.2 Ho, and H2 performance constraint
209(1)
7.2.3 Poles assignment
210(1)
7.2.4 Control objective
211(1)
7.3 Improved mixed H2/H∞ control law
211(8)
7.3.1 Some lemmas
211(2)
7.3.2 H2 control
213(4)
7.3.3 Mixed H2/H∞ control
217(2)
7.4 Simulation test
219(11)
7.4.1 Simulation results using static output feedback controller
220(2)
7.4.2 Simulation results using improved mixed H2/Hoo controller
222(5)
7.4.3 Simulation results using a traditional mixed H2/Hx controller
227(3)
7.4.4 Comparison analysis using different controllers
230(1)
7.5 Conclusions
230(3)
References
231(2)
8 Nonfragile H∞ control with input constraints
233(50)
8.1 Introduction
233(3)
8.2 Problem formulation
236(10)
8.2.1 Attitude system description of flexible spacecraft
236(2)
8.2.2 Passive and active vibration suppression cases
238(2)
8.2.3 Brief introduction on piezoelectric actuators
240(3)
8.2.4 Improved model and control objective
243(3)
8.3 Nonfragile HK control law
246(6)
8.3.1 Sufficient conditions under additive perturbation
246(4)
8.3.2 Sufficient conditions under multiplicative perturbation
250(2)
8.4 Simulation test
252(27)
8.4.1 Comparisons of control performance under additive perturbation
254(10)
8.4.2 Comparisons of control performance under multiplicative perturbation
264(10)
8.4.3 Simulation comparison analysis
274(5)
8.5 Conclusions
279(4)
References
280(3)
9 Antidisturbance control with active vibration suppression
283(40)
9.1 Introduction
283(2)
9.2 Problem formulation
285(8)
9.2.1 Attitude dynamics modeling
285(7)
9.2.2 Preliminaries
292(1)
9.2.3 Control objective
293(1)
9.3 Antidisturbance control law with input magnitude, and rate constraints
293(16)
9.3.1 Stochastically intermediate observer design
293(2)
9.3.2 Antidisturbance controller design
295(1)
9.3.3 Sufficient conditions for uniform ultimate boundedness
296(3)
9.3.4 Sufficient conditions for H∞ control strategy
299(2)
9.3.5 Sufficient conditions for input magnitude, and rate constraints
301(8)
9.4 Simulation test
309(11)
9.4.1 Simulation results using an antidisturbance controller
311(6)
9.4.2 Simulation results using a mixed H2/H∞ controller
317(3)
9.5 Conclusions
320(3)
References
320(3)
10 Chaotic attitude tracking control
323(14)
10.1 Introduction
323(1)
10.2 Problem formulation
324(6)
10.2.1 Chaotic attitude dynamics
324(2)
10.2.2 Chaotic system characteristics and chaotic attractor
326(1)
10.2.3 Tracking error dynamics and control objective
326(4)
10.3 Adaptive variable structure control law
330(2)
10.4 Simulation test
332(3)
10.5 Conclusions
335(2)
References
335(2)
11 Underactuated chaotic attitude stabilization control
337(24)
11.1 Introduction
337(2)
11.2 Problem formulation
339(5)
11.2.1 Chaotic attitude system description
339(1)
11.2.2 Two examples of Chen and Lu systems
340(2)
11.2.3 Control objective
342(2)
11.3 Sliding mode control law
344(4)
11.3.1 Reference trajectory design
344(1)
11.3.2 Controller design
345(3)
11.4 Simulation test
348(9)
11.4.1 Simulation results for the failure of one actuator
349(2)
11.4.2 Simulation results for failure of two actuators
351(6)
11.5 Conclusions
357(4)
References
357(4)
Index 361
Chuang Liu is an Associate Professor at Northwestern Polytechnical University, China. He is also Scientific Committee Member of Aeromeet 2022. He received the COSPAR Outstanding Paper Award for Young Scientists in 2020. His research focuses on aerospace engineering. Xiaokui Yue is a Professor at Northwestern Technical University, China. His research has focused on the frontiers of space exploration and on computational methods for nonlinear dynamical systems. Keke Shi is a Research Assistant at the Harbin Institute of Technology, China. His research is focused on overall spacecraft design and dynamics control. Zhaowei Sun is a Professor at the Harbin Institute of Technology, China. His research focuses on overall spacecraft dynamics and control.
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