基于约束粒子群算法的直流电机速度控制pi - λ δ控制器设计

Ayan Roy, S. Srivastava
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引用次数: 18

摘要

本文研究并提出了一种基于约束粒子群优化(CPSO)的分数阶PID (PIλDδ)控制器参数确定的新设计方法,用于永磁直流电动机的速度控制。λ d δ是传统PID的一种形式,其积分和微分阶数是分数阶而不是整数阶。设计目标是在相位裕度、上升时间、稳定时间等频域和时域约束条件下优化系统的性能。CPSO算法得到PIλDδ的5个参数满足所有约束条件的可行解。将所提出的控制器与广泛使用的ZN整定PID控制器在系统暂态响应和鲁棒性方面进行了对比研究。此外,还给出了系统在不同约束条件下的输出。仿真结果表明,该方法能提高闭环性能。
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Design of optimal PIλDδ controller for speed control of DC motor using constrained particle swarm optimization
In this paper, a novel design method for determining the parameters of an optimal Fractional Order PID (PIλDδ) controller for speed control of a Permanent Magnet DC (PMDC) motor using Constrained Particle Swarm Optimization (CPSO) is studied and presented. A PλDδ is a form of conventional PID whose orders of integration and differentiation are fractional number instead of integers. The design objective was to optimize the performance of the system subject to different constraints in frequency and time domain such as phase margin, rise time, settling time etc. CPSO algorithm yields feasible solution of five parameters of PIλDδ satisfying all the required constraints. A comparative study has been carried out on the basis of transient response and robustness of system using proposed controller with widely used ZN tuned PID controller. Moreover, the output of the system for different sets of constraints has been presented. It is shown from simulation results that the proposed method yields more improved closed loop performance.
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