Design of Adaptive Global Barrier-Function PID-Type Finite Time Tracking Control Method for Uncertain Systems

This article presents a novel adaptive control methodology for achieving robust and accurate tracking control of uncertain nonlinear systems using a combination of barrier functions, global sliding mode control, proportional-integral-derivative (PID) controllers, and finite time control techniques. The proposed adaptive barrier-function global PID-type control method is designed to handle both matched and unmatched uncertainties and adjust the control parameters in real time to account for changes in system dynamics and perturbations. It efficiently handles both matched and mismatched uncertainties, ensuring precise tracking performance even amid uncertain dynamics and disturbances. The methodology dynamically adjusts control parameters in real time to accommodate changes in system dynamics, enhancing adaptability and performance. The globality of the suggested controller ensures the absence of a reaching phase and establishes the presence of the sliding mode around the surface right from the beginning. The proposed method has also been expanded to address uncertain dynamic systems with both matched and unmatched disturbances, while accounting for actuator faults and input saturation. The efficacy of the proposed methodology is demonstrated through simulation studies and experimental results on a rotary inverted pendulum (RIP) system, showcasing rapid convergence and exceptional tracking capabilities in practical scenarios. The contributions of this research lie in presenting a novel methodology that significantly contributes to the field of nonlinear control systems, offering a robust framework capable of addressing uncertainties in complex nonlinear systems. The results show that the method achieves fast convergence and excellent tracking performance in the presence of uncertainties and disturbances. The proposed adaptive control methodology stands as a promising approach for overcoming the complexities involved in controlling uncertain nonlinear systems, paving the way for advancements in robust control methodologies.