Research On PID Parameters Optimization-based Bacterial Swarm Foraging Optimization Algorithm For Electro-hydraulic Position System

PID controller is widely used in various industrial control circumstances due to itssimple structure, easy implement, good control effect and strong robustness features.However, it’s often difficult for the traditional PID controller to obtain satisfied controlperformance. Because once the controller’s parameters are set, they can’t be changed.Additionally, since the system, in practice, is affected by some factors such astime-varying, non-linearity and uncertainties, etc, it is often hard for the controller toachieve satisfied control performance. Fortunately, the development of intelligent controltheory offers solutions for the aforementioned control problems. A variety of intelligentPID controllers can be formed by combining conventional PID controller with intelligentcontrol technology and strengthening their own merits and complementing each other.Intelligent bionic algorithm is one of the most important parts of intelligent control. Bycombining bionic algorithms with PID algorithms, bionics algorithm PID control theoryhas several advantages, for instance, independence from exact mathematical model in thesystem, good adaptation and robustness, Therefore the research of bionics algorithm PIDcontroller has profound practical significance.To overcome the shortages of slow convergence in bacterial foraging (BF) algorithmand premature in particle swarm optimization (PSO) algorithm, a bacterial swarm foragingoptimization (BSFO) algorithm was proposed. Inspired by the information sharingmechanism in PSO algorithm, the velocity updating formula in PSO was used to replacethe direction vector of position formula in BF algorithm, therefore each bacterium had theability of perceiving the position of the neighborhood bacteria and moving to the historicalbest position of the whole swarm. The optimal results of eight benchmark test functionsshowed that the BSFO algorithm had better performance for most of the functions,compared with BF algorithm, μPSO algorithm and bacterial swarm optimization (BSO)algorithm.Based on the above, the BSFO algorithm was respectively applied to the PIDcontroller’s parameters optimization in the valve-controlled symmetrical and asymmetrical hydraulic cylinder electro-hydraulic position servo system. In the environment ofMATLAB, the simulation results indicated that the PID control system, when adopting theBSFO algorithm, had advantages of faster response, higher convergence precision andsmaller overshoot, compared to the others optimization algorithm on PID control system.In AMESim/Simulink environment, the results of the simulation indicated that thebacterial swarm foraging optimization PID controller had good adaptation and robustness.According to the experimental research on the computer control system which is based onLabview, and the comparison with the traditional PID control strategy, the result indicatedthat the bacterial swarm foraging optimization PID control strategy could well satisfy thevalve-controlled asymmetrical hydraulic cylinder system’s dynamic performancerequirements.