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首页> 外文会议>2010 International Conference on Logistics Systems and Intelligent Management >Tuning PID control parameters on hydraulic servo control system based on chaos quantum-behaved particle swarm optimization algorithm
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Tuning PID control parameters on hydraulic servo control system based on chaos quantum-behaved particle swarm optimization algorithm

机译：基于混沌量子行为粒子群算法的液压伺服控制系统PID控制参数整定

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摘要

The PID control parameters are very important to performance of hydraulic servo control system and how to find rapidly the optimum values of PID control parameters is very difficult problem. To overcome the problem of low convergence speed and sensitivity to local convergence with the traditional quantum-behaved particle swarm optimization (QPSO) to handle optimum problem, a novel method of judging the local convergence by the variance of the population's fitness was proposed, and the chaos quantum-behaved particle swarm optimization algorithm (CQPSO) was proposed. The program CQPSO1.0 was developed. Based on Matlab/simulink software and taking the IATE standards of optimization design as objective function, the proposed method was applied for the optimization of the three parameters of PID controller of electric-hydraulic servo system of 6-DOF parallel platform. Simulation results show that the proposed parameter optimum method is an effective tuning strategy and has good performance.
机译：PID控制参数对液压伺服控制系统的性能非常重要，如何快速找到PID控制参数的最优值是一个非常困难的问题。为了解决传统量子行为粒子群算法（QPSO）收敛速度慢，对局部收敛敏感的问题，提出了一种基于总体适应度方差判断局部收敛的新方法，提出了混沌量子行为粒子群优化算法（CQPSO）。开发了程序CQPSO1.0。在Matlab / simulink软件的基础上，以优化设计的IATE标准为目标函数，将该方法应用于6-DOF并联平台电液伺服系统PID控制器三个参数的优化。仿真结果表明，所提出的参数优化方法是一种有效的调整策略，具有良好的性能。

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