Dual Flexible Prescribed Performance Control of Input Saturated High-Order Nonlinear Systems.

Area of Science:

• Control Engineering
• Nonlinear Systems Theory
• Robotics

Background:

• Existing prescribed performance control (PPC) methods for input-saturated high-order nonlinear systems (IS-HONSs) often use fixed performance constraint boundaries (PCBs), limiting initial error tolerance.
• These methods frequently overlook the interplay between performance constraints and input saturation, leading to fragility when saturation occurs.

Purpose of the Study:

• To develop a dual flexible prescribed performance control (DFPPC) approach for IS-HONSs.
• To enhance the robustness of control systems against initial conditions and input saturation.
• To ensure accurate tracking performance while maintaining errors within adaptable boundaries.

Main Methods:

• Design of novel tensile model-based PCBs that dynamically adjust based on output and input constraints.
• Development of an adaptive mechanism for PCBs to extend during input saturation and restore afterward.
• Parameter adjustment to accommodate various initial errors.

Main Results:

• The proposed DFPPC method demonstrates resilience to diverse initial conditions.
• It effectively balances input saturation and performance constraints by adaptively adjusting PCBs.
• Guarantees semi-global boundedness of all closed-loop signals and accurate tracking within PCBs.

Conclusions:

• The DFPPC algorithm offers a robust solution for controlling IS-HONSs.
• It ensures stable system performance and precise tracking even under input saturation.
• The adaptive nature of PCBs enhances the practical applicability of the control strategy.