首页> 外文会议>Computer Modelling and Simulation, 2009. UKSIM '09 >Adaptive Tuning of a PID Speed Controller for DC Motor Drives Using Multi-objective Particle Swarm Optimization
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Adaptive Tuning of a PID Speed Controller for DC Motor Drives Using Multi-objective Particle Swarm Optimization

机译:基于多目标粒子群算法的直流电动机PID速度控制器自适应调整

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In this paper, a control scheme based on Multi-Objective Particle Swarm optimization MOPSO is proposed, which is able to tune the PID controller parameters simultaneously in order to find the set of trade-off optimal solutions that is called Pareto-set optimization solution of the conflicting objective functions for DC motor drive system. Multi Objective Particle Swarm Optimization MOPSO is implemented to tackle a number of conflicting goals that define the optimality problem. This paper deals with five conflicting objective functions. These conflicting functions are: 1. Minimize the maximum overshoot, 2. Minimize the rise time, 3. Minimize speed tracking error, 4. Minimize the steady state error, and 5. Minimize the settling time.
机译:本文提出了一种基于多目标粒子群优化算法MOPSO的控制方案,该方案能够同时调整PID控制器参数,以找到折衷的最优解集,称为Pareto集最优解。直流电动机驱动系统的目标功能冲突。多目标粒子群优化MOPSO的实现旨在解决定义最优性问题的许多相互冲突的目标。本文讨论了五个相互矛盾的目标函数。这些冲突功能是:1.最小化最大过冲; 2.最小化上升时间; 3.最小化速度跟踪误差; 4.最小化稳态误差;以及5.最小化稳定时间。

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