Adaptive Fuzzy Asymptotic Tracking for Nonlinear Systems With Nonstrict-Feedback Structure
IEEE Transactions on Cybernetics
|July 4, 2020
Summary
This study introduces a new nonlinear adaptive control method for non-strict feedback systems. The approach ensures tracking errors converge to zero and system stability, outperforming existing methods.
Area of Science:
- Control Engineering
- Nonlinear Systems Theory
- Adaptive Control
Background:
- Nonlinear systems with non-strict feedback present significant control challenges.
- Existing adaptive tracking control schemes often struggle with unknown parameters and nonlinearities.
Purpose of the Study:
- To develop a novel nonlinear adaptive control law for non-strict feedback systems.
- To address challenges posed by unknown virtual control parameters and uncertain nonlinearities.
- To guarantee asymptotic stability and bounded signals for the controlled system.
Main Methods:
- Integration of the backstepping technique with a bound estimation method.
- Design of a new nonlinear adaptive asymptotical control law.
- Development of an improved Lyapunov function incorporating lower bounds of control parameters.
Main Results:
- The proposed control law effectively offsets unknown parameters and nonlinearities.
- Tracking control error converges asymptotically to zero.
- All system signals, including state variables and adaptive laws, remain bounded.
- Asymptotic stability of the nonlinear system is achieved.
Conclusions:
- The presented adaptive control method offers a robust solution for nonlinear non-strict feedback systems.
- The novel approach guarantees superior performance in terms of tracking accuracy and system stability.
- Simulation results validate the effectiveness and practical applicability of the proposed control strategy.
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