Intelligent Autonomous Control of Spacecraft with Multiple Constraints

Preface
Acknowledgements
Contents
Acronyms
1 Introduction
1.1 Review of Spacecraft Motion Planning
1.1.1 Geometric Method
1.1.2 Artificial Potential Function Method
1.1.3 Discretized Method
1.1.4 Randomized Planning Method
1.1.5 Optimization-Based Method
1.1.6 Artificial Intelligence-Based Method
1.2 Review of Spacecraft Attitude and Position Control
1.2.1 Adaptive Control of Spacecraft
1.2.2 Anti-Disturbance Control of Spacecraft
1.2.3 Fault-Tolerant Control of Spacecraft
1.2.4 State-Constrained Control of Spacecraft
1.2.5 Intelligent Control of Spacecraft
1.3 Contents of the Book
References
2 Dynamics Modeling and Mathematical Preliminaries
2.1 Introduction
2.2 Notations
2.3 Coordinate Frames
2.4 Mathematical Models of Spacecraft Dynamics
2.4.1 Spacecraft Attitude Dynamics
2.4.2 Spacecraft Relative Position Dynamics
2.4.3 Spacecraft Relative Position-Attitude Coupled Dynamics
2.4.4 Dual-Quaternion-Based Spacecraft Relative Motion Dynamics
2.5 Lyapunov Stability Theory
References
3 Data-Driven Adaptive Control for Spacecraft Constrained Reorientation
3.1 Introduction
3.2 Problem Statement
3.2.1 Attitude Constraints
3.2.2 Angular Velocity Constraints
3.2.3 Problem Statement and Challenges
3.3 I&I Adaptive Attitude Control
3.3.1 Regressor Reconfiguration
3.3.2 I&I Adaptive Controller Design
3.4 Data-Driven I&I Adaptive Control
3.4.1 Filtered System Dynamics
3.4.2 Data-Driven Adaptive Extension
3.5 Numerical Simulations
3.5.1 Performance Validation
3.5.2 Comparison Results
3.5.3 Robustness Tests
3.6 Hardware-in-Loop Experiments
3.7 Summary
References
4 Learning-Based Fault-Tolerant Control for Spacecraft Constrained Reorientation Maneuvers
4.1 Introduction
4.2 Adaptive FTC for Spacecraft Constrained Reorientation
4.2.1 Problem Formulation
4.2.2 Adaptive FTC Under Attitude Constraints
4.2.3 Adaptive FTC Under Attitude and Angular Velocity Constraints
4.2.4 Numerical Simulations
4.3 Learning-Based Optimal FTC for Spacecraft Constrained Reorientation
4.3.1 Problem Formulation
4.3.2 Constrained Optimal FTC Design
4.3.3 Single-Critic NN Design and Stability Analysis
4.3.4 Numerical Simulations
4.4 Summary
References
5 Intelligent Fault Diagnosis and Fault-Tolerant Control of Spacecraft
5.1 Introduction
5.2 Preliminaries
5.3 Disturbance Observation Scheme
5.4 Fault Diagnosis Scheme
5.4.1 Fault Diagnosis Using Addaptive Estimator
5.4.2 Fault Diagnosis Using Neural Network
5.5 Fault-Tolerant Control
5.6 Numerical Simulation
5.6.1 Disturbances Model
5.6.2 Simulation Conditions
5.6.3 Simulation of Disturbance Observation Scheme
5.6.4 Simulation of Fault Diagnosis Scheme
5.6.5 Simulation of Fault-Tolerant Control Scheme
5.7 Summary
References
6 Reinforcement Learning-Based Dynamic Control Allocation for Spacecraft Attitude Stabilization
6.1 Introduction
6.2 Problem Formulation
6.3 Dynamic Control Allocation Scheme
6.3.1 Cost Function
6.3.2 Optimal Manipulation Law Based on Reinforcement Learning
6.3.3 Parameters Solving Based on Neural Network
6.4 Simulation
6.4.1 Simulation of Singularity Problem
6.4.2 Simulation of Dynamic Control Allocation
6.5 Summary
References
7 Learning-Based Adaptive Optimal Event-Triggered Control for Spacecraft Formation Flying
7.1 Introduction
7.2 Problem Formulation
7.3 Event-Based Adaptive Optimal Control
7.3.1 Continuous Near Optimal Tracking Control Law
7.3.2 Event-Triggered Mechanism
7.3.3 Stability Analysis
7.3.4 Zeno-Free Analysis
7.4 Numerical Simulations
7.5 Summary
References
8 Adaptive Prescribed Performance Pose Control of Spacecraft Under Motion Constraints
8.1 Introduction
8.2 Problem Formation
8.2.1 Relative Position Tracking
8.2.2 Boresight Pointing Adjustment
8.3 Problem Solution
8.3.1 Prescribed Performance
8.3.2 Non-CE Adaptive Pose Control
8.4 Numerical Simulations
8.4.1 Nominal Simulation Campaign
8.4.2 Practical Simulation Campaign
8.4.3 Monte Carlo Simulation Campaign
8.5 Summary
References
9 I&I Adaptive Pose Control of Spacecraft Under Kinematic and Dynamic Constraints
9.1 Introduction
9.2 Problem Formulation
9.2.1 Relative Position Tracking
9.2.2 Boresight Pointing Adjustment
9.2.3 Challenges
9.3 Adaptive Controller Design
9.3.1 I&I Adaptive Position Controller
9.3.2 I&I Adaptive Attitude Controller
9.3.3 Discussion
9.4 Numerical Simulations
9.4.1 Baseline Simulation Configuration
9.4.2 Ideal Simulation Scenario
9.4.3 Practical Simulation Scenario
9.5 Summary
References
10 Composite Learning Pose Control of Spacecraft with Guaranteed Parameter Convergence
10.1 Introduction
10.2 Preliminaries
10.2.1 Gradient Descent Estimator
10.2.2 Dynamic Regressor Extension and Mixing
10.3 Composite Learning Pose Control
10.3.1 Filtered System Dynamics
10.3.2 Traditional Composite Adaptive Law
10.3.3 Composite Learning Law
10.4 Numerical Simulations
10.4.1 Ideal Simulation Campaign
10.4.2 Practical Simulation Campaign
10.5 Summary
References
11 Reinforcement Learning-Based Pose Control of Spacecraft Under Motion Constraints
11.1 Introduction
11.2 Problem Formulation
11.2.1 Motion Constraints
11.2.2 Control Objective
11.3 Learning-Based Pose Control
11.3.1 Reward Function Design
11.3.2 Optimal Control Solution Analysis
11.3.3 Online Learning Control Algorithm
11.3.4 Initial Control Policy
11.4 Numerical Simulations
11.4.1 Point to Point Maneuvers Without Constraints
11.4.2 Docking to the Target with Constraints
11.4.3 Monte-Carlo Simulations
11.5 Summary
References
Appendix Conclusion
A.1 General Conclusion
A.2 Future Work