Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust...

Area of Science:

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

Background:

• Servo systems often exhibit saturation and dead zone nonlinearities, complicating control design.
• Integral component second-order models require advanced control strategies for optimal performance.
• Existing methods struggle to balance robustness and performance in nonlinear systems.

Purpose of the Study:

• To develop a new generation of optimal Proportional-Integral (PI) controllers for servo systems with static nonlinearities.
• To propose an effective anti-windup scheme addressing integrator wind-up and dead zone compensation.
• To ensure robust stability and controller robustness against process parametric variations.

Main Methods:

• Formulation of objective functions based on integral of time multiplied by absolute error and sensitivity functions.
• Application of the extended symmetrical optimum (ESO) method with a single design parameter.
• Development of a back-calculation and tracking anti-windup scheme.
• Optimization using an adaptive Gravitational Search Algorithm (GSA) with inequality constraints for robust stability.

Main Results:

• Optimal PI controllers designed for nonlinear servo systems.
• An effective anti-windup strategy that compensates for integrator wind-up and dead zone.
• Guaranteed robust stability and controller robustness through constrained optimization.
• Experimental validation on a laboratory servo system for angular position control.

Conclusions:

• The proposed PI controller tuning method offers an efficient approach to designing resilient control systems.
• The adaptive GSA-based tuning effectively optimizes PI controllers for challenging servo system applications.
• The developed control strategy demonstrates superior performance and robustness in experimental settings.