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Adaptive fuzzy control for strict-feedback canonical nonlinear systems with H/sub /spl infin// tracking performance
Summary
This study introduces an adaptive fuzzy controller for nonlinear systems with unknown dynamics and disturbances. The controller ensures robust tracking performance, demonstrating its practical applicability through simulations.
Area of Science:
- Control Engineering
- Nonlinear Systems Theory
- Fuzzy Logic Systems
Background:
- Strict-feedback canonical nonlinear systems often exhibit unknown nonlinearities and external disturbances.
- Traditional control methods may struggle with uncertainties inherent in these systems.
- Fuzzy logic systems offer powerful function approximation capabilities for handling nonlinearities.
Purpose of the Study:
- To propose an adaptive fuzzy controller for strict-feedback canonical nonlinear systems.
- To address completely unknown nonlinearities and disturbances.
- To achieve robust tracking performance despite system uncertainties.
Main Methods:
- Employing adaptive fuzzy control theory to design the control law.
- Utilizing fuzzy logic systems for uniform approximation of unknown nonlinear functions.
- Incorporating H-infinity tracking performance to mitigate modeling errors and disturbances.
Main Results:
- Development of a novel adaptive fuzzy controller for a class of nonlinear systems.
- Demonstrated ability to handle unknown nonlinearities and disturbances effectively.
- Simulation results confirm the controller's applicability and performance.
Conclusions:
- The proposed adaptive fuzzy controller is effective for strict-feedback nonlinear systems.
- H-infinity tracking performance enhances robustness against uncertainties.
- The method provides a viable approach for controlling complex nonlinear systems.
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