On Safe Sliding Mode Control Design for Nonlinear Uncertain Systems.

Area of Science:

• Control Systems Engineering
• Nonlinear System Analysis
• Robotics and Automation

Background:

• Nonlinear uncertain systems pose significant challenges for achieving both stability and safety.
• Existing control strategies often struggle to balance robust stability with strict safety constraint enforcement.
• The integration of control barrier functions (CBF) offers a promising framework for safety-critical control.

Purpose of the Study:

• To introduce a novel safe sliding mode controller (SSMC) for nonlinear uncertain systems.
• To develop a controller that guarantees robust asymptotic stability and enforces safety constraints simultaneously.
• To reduce the computational burden associated with safety-critical control design.

Main Methods:

• A dual-loop architecture combining an inner sliding mode controller and an outer safeguarding loop.
• Augmentation of the system with a state variable derived from Lyapunov theory to establish a CBF framework.
• Development of a noninvasive safeguarding control with a risk-set-triggered mechanism and closed-form control input expressions, avoiding quadratic programming (QP).

Main Results:

• Theoretical analysis confirms the controller ensures system stability and robust safety under matched uncertainties.
• Simulation studies demonstrate the controller's ability to maintain safety without significant performance degradation.
• The proposed controller exhibits superior computational efficiency compared to QP-based safety-critical controllers.

Conclusions:

• The developed safe sliding mode controller effectively guarantees stability and safety in nonlinear uncertain systems.
• The innovative design, particularly the avoidance of QP, offers significant computational advantages.
• This approach provides a robust and efficient solution for safety-critical control applications.