Observer-Based Adaptive Fuzzy Control for Nonlinear State-Constrained Systems Without Involving Feasibility
IEEE Transactions on Cybernetics
|June 24, 2021
Summary
This study introduces an adaptive output feedback control strategy for nonlinear systems with unmeasured states and full-state constraints. The method ensures system stability and good tracking performance by estimating unmeasured states and directly satisfying constraints.
Area of Science:
- Control Theory
- Nonlinear Systems
- State Estimation
Background:
- Nonlinear systems with unmeasured states pose control challenges.
- Full-state constraints can degrade performance and stability.
- Existing barrier Lyapunov functions have feasibility limitations.
Purpose of the Study:
- Develop an adaptive output feedback control strategy.
- Address unmeasured states and full-state constraints.
- Ensure system stability and tracking performance.
Main Methods:
- A stable state observer estimates unmeasured states.
- Nonlinear mappings are employed to satisfy full-state constraints directly.
- Lyapunov theorem is used to prove closed-loop stability.
Main Results:
- The developed strategy effectively estimates unmeasured states.
- Full-state constraints are satisfied without intermediate controller feasibility conditions.
- The closed-loop system stability is rigorously proven.
Conclusions:
- The proposed adaptive output feedback control is effective for nonlinear systems with unmeasured states and constraints.
- Simulation results validate the strategy's performance and stability.
- This approach overcomes limitations of existing barrier Lyapunov functions.
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