Ultra-high-precision pneumatic force servo system based on a novel improved particle swarm optimization algorithm integrating Gaussian mutation and fuzzy theory

Abstract

In this study, an ultra-high-precision pneumatic force servo system (UPFSS) is proposed. On the one hand, a novel air-floating pneumatic cylinder (AFPC) with an air-floating piston capable of independent air supply and exhaust is developed for this system, and its special flow channel design allows the air-floating piston to be suspended in the cylinder without being constrained by the pressure in the chambers. The friction force of the AFPC is less than 0.0049 N. On the other hand, a leakage chamber is constructed to simulate the clearance between the air-floating piston and the cylinder wall, and a fuzzy proportional integral (FPI)-based pressure control system (PCS) is designed for the simulated leakage chamber. Furthermore, a novel particle swarm optimization algorithm integrating Gaussian mutation and fuzzy theory (IGF-PSO) is presented. After testing, the IGF-PSO algorithm is found to have outstanding optimization performance. Then, the parameters of the FPI controller are optimized through the IGFPSO algorithm. Experimental comparisons reveal that the steady-state error achieved by the parameter-optimized pressure controller in response to the leakage condition is about 38 % smaller than that achieved by the pressure controller with parameters obtained using the trial-and-error method. Finally, the UPFSS is tested by using the optimized PCS to supply compressed air to the chamber of the AFPC. The results show that the UPFSS achieves a steady-state error of no more than 0.0279 N in the continuous step response within the range of 240 N.