Optimal Pneumatic Actuator Positioning and Dynamic Stability using Prescribed Performance Control with Particle Swarm Optimization: A Simulation Study
(1) * Addie Irawan Mail (Universiti Malaysia Pahang, Malaysia)
(2) Mohd Syakirin Ramli Mail (Universiti Malaysia Pahang, Malaysia)
(3) Mohd Herwan Sulaiman Mail (Universiti Malaysia Pahang, Malaysia)
(4) Mohd Iskandar Putra Azahar Mail (Universiti Malaysia Pahang, Malaysia)
(5) Abdul Hamid Adom Mail (Universiti Malaysia Perlis, Malaysia)
*corresponding author

Abstract


This paper introduces an optimal control strategy for pneumatic servo systems (PSS) positioning using Finite-time Prescribed Performance Control (FT-PPC) with Particle Swarm Optimization (PSO). Pneumatic servo systems are widely used in industrial automation, as well as medical and cybernetics systems that involve robotics applications. Precision in pneumatic control is crucial not only for the sake of efficiency but also safety. The primary goal of the proposed control strategy is to optimize the convergence rate and finite time of the prescribed performance function in error transformation of the FT-PPC, as well as the Proportional, Integral and Derivative (PID) controller as the inner-loop controller for this system. The study utilizes a dynamic model of a pneumatic proportional valve with a double-acting cylinder (PPVDC) as the targeted plant and performs simulations with a multi-step input trajectory. This offline tuning method is essential for such nonlinear systems to be safely optimized, avoiding major damage to the real-time fine-tuned works on the controller. The results demonstrate that the proposed control strategy surpasses the performance of FT-PPC with a PID controller alone, significantly improving the system's performance, including suppressing overshoot and oscillation in the responses. Further validation through the actual system of PPVDC using the fine-tuned values of FT-PPC and PID with PSO is a future task and more challenging to come, as hardware constraints may vary with different environments such as temperatures.

Keywords


Pneumatic actuator; Prescribed performance control; Swarm intelligence; Metaheuristic

   

DOI

https://doi.org/10.31763/ijrcs.v3i3.1002 		      

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