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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

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Full-state time-varying asymmetric constraint control for non-strict feedback nonlinear systems based on dynamic

Zhongjun Yang¹, Chuyan Dong², Xinyu Zhang¹

¹College of Information Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, People's Republic of China.

Scientific Reports

|June 21, 2022

Summary

This study introduces an adaptive fuzzy controller for nonlinear systems with constraints and disturbances. The new method ensures fast, stable tracking while respecting system limitations.

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Area of Science:

Nonlinear control systems
Adaptive control theory
Fuzzy logic systems

Background:

Non-strict feedback nonlinear systems present challenges in control design.
External disturbances and time-varying asymmetric full state constraints complicate tracking control.
Traditional control methods struggle with computational complexity and constraint violations.

Purpose of the Study:

To develop an adaptive fuzzy controller for nonlinear systems with external disturbances and asymmetric state constraints.
To address the computational explosion problem in backstepping control design.
To enhance tracking speed and stability under constrained conditions.

Main Methods:

Fuzzy logic systems are used to estimate unknown nonlinear terms and external disturbances.
A backstepping method is employed for adaptive fuzzy controller design.
An improved log-type time-varying asymmetric barrier Lyapunov function (TABLF) is introduced to handle state constraints.
Dynamic surface control (DSC) is integrated to mitigate the controller's computational burden.

Main Results:

The proposed control scheme effectively estimates system uncertainties and disturbances.
The integration of DSC and TABLF ensures that state constraints are not violated.
The controller demonstrates accelerated tracking speed and stable convergence.
Simulations confirm the controller's robust performance under external disturbances.

Conclusions:

The developed adaptive fuzzy controller with DSC and TABLF offers a robust solution for tracking control in constrained nonlinear systems.
The approach successfully balances performance, stability, and constraint satisfaction.
This method provides a significant improvement over existing techniques for similar control problems.