Sliding Mode Control with Fuzzy Boundary Layer for a Class of Uncertain Nonlinear Systems
Xiaolong Chen
Abstract
Xiaolong Chen
Abstract
The saturation function control method is effective for reducing the sliding mode chattering.The boundary layer should be adjusted adaptively so as to achieve a trade-off between tracking precision and robustness to unmodeled dynamics.A fuzzy controller was designed to regulate the thickness of boundary layer.The fuzzy controller adopted the distance to sliding surface s and the angle θ between the sliding surface and the state vector.The method was applied to the control of a second order uncertain nonlinear system.Simulation results show system chattering is eliminated, the thickness of boundary layer is optimized, system tracking error is reduced, and the tracking performance of the controlled system is better than that of two methods:the method of boundary layer adaptive regulation and the method of boundary layer approach angle regulation.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The saturation function control method is effective for reducing the sliding mode chattering.The boundary layer should be adjusted adaptively so as to achieve a trade-off between tracking precision and robustness to unmodeled dynamics.A fuzzy controller was designed to regulate the thickness of boundary layer.The fuzzy controller adopted the distance to sliding surface s and the angle θ between the sliding surface and the state vector.The method was applied to the control of a second order uncertain nonlinear system.Simulation results show system chattering is eliminated, the thickness of boundary layer is optimized, system tracking error is reduced, and the tracking performance of the controlled system is better than that of two methods:the method of boundary layer adaptive regulation and the method of boundary layer approach angle regulation.
Key concepts: Control theory (sociology), Robustness (evolution), Sliding mode control, Boundary layer, Nonlinear system, Fuzzy logic, Fuzzy control system, Boundary (topology)