Quantized controller for a class of uncertain nonlinear systems with dead-zone nonlinearity.

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Robotics

Background:

• Uncertain nonlinear systems present significant control challenges due to unknown parameters, disturbances, and actuator nonlinearities like dead-zones.
• Existing control methods often struggle with high computational complexity when dealing with multiple uncertainties.

Purpose of the Study:

• To design a quantized controller for a class of uncertain nonlinear systems with unknown disturbances and dead-zone nonlinearity.
• To reduce computational cost by estimating the maximum upper bound of disturbances instead of individual disturbances.

Main Methods:

• A novel quantized controller is designed for strict feedback nonlinear systems.
• Tuning functions are developed to estimate unknown system parameters and disturbance bounds.
• A backstepping technique is employed for controller and tuning function design.
• Lyapunov stability theory is used to prove the controller's stability.

Main Results:

• The proposed quantized controller effectively stabilizes uncertain nonlinear systems.
• The method reduces computational complexity by estimating disturbance bounds.
• MATLAB simulations confirm the controller's performance and stability.

Conclusions:

• A computationally efficient quantized controller is presented for uncertain nonlinear systems.
• The controller robustly handles unknown disturbances and dead-zone nonlinearities.
• The backstepping approach combined with Lyapunov stability ensures system stabilization.