Event-triggered fault-tolerant control for input-constrained nonlinear systems with mismatched disturbances via
Heng Zhao1, Huanqing Wang2, Ben Niu3
1College of Control Science and Engineering, Bohai University, Jinzhou, Liaoning 121013, China.
Summary
This study introduces an event-triggered optimal fault-tolerant control for nonlinear systems. The novel adaptive dynamic programming approach ensures system stability and optimal performance despite faults and disturbances.
Area of Science:
- Control Engineering
- Nonlinear Systems Theory
- Adaptive Dynamic Programming
Background:
- Investigates event-triggered optimal fault-tolerant control for input-constrained nonlinear systems.
- Addresses challenges posed by mismatched disturbances and abrupt faults.
Purpose of the Study:
- Develop a sliding mode fault-tolerant control strategy using adaptive dynamic programming (ADP).
- Ensure optimal performance and stability for general nonlinear dynamics under fault conditions.
Main Methods:
- Employs an adaptive dynamic programming (ADP) algorithm for fault-tolerant control.
- Utilizes a single critic neural network (NN) to solve the Hamilton-Jacobi-Bellman (HJB) equation.
- Applies experience replay to overcome persistence of excitation (PE) condition challenges.
Main Results:
- Proposes a novel control method to effectively eliminate abrupt fault effects.
- Achieves optimal control with minimum cost using a single network architecture.
- Proves uniform ultimate boundedness of the closed-loop nonlinear system via Lyapunov stability theory.
Conclusions:
- The developed control strategy effectively handles faults and disturbances in nonlinear systems.
- The method ensures optimal performance and stability, validated by simulation examples.
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