Structured mixed-sensitivity H∞ design using Particle Swarm Optimization

S. Bouallègue, Joseph Haggège, M. Benrejeb
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引用次数: 12

Abstract

In this paper, a new structured mixed-sensitivity ℋ∞ design approach, using Particle Swarm Optimization (PSO) technique, is proposed. The case study of an electrical DC drive benchmark is adopted to illustrate the efficiency and viability of the proposed control approach. The optimization based synthesis problem is formulated and solved by a constrained PSO algorithm. In the proposed control strategy, a PID controller's structure is adopted. Simulations and experimental results show the advantages of simple structure, lower order and robustness of the proposed controller. A comparison to another similar evolutionary algorithm, such as Genetic Algorithm (GA), shows the superiority of the PSO-based method to solve the formulated optimization problem.
基于粒子群优化的结构混合灵敏度H∞设计
提出了一种基于粒子群优化(PSO)的结构混合灵敏度h∞设计方法。以直流电机驱动基准为例,验证了所提控制方法的有效性和可行性。提出了基于优化的综合问题,并用约束粒子群算法求解。在所提出的控制策略中,采用了PID控制器的结构。仿真和实验结果表明,该控制器结构简单、阶数低、鲁棒性好。通过与遗传算法(GA)等类似进化算法的比较,证明了基于粒子群算法求解公式优化问题的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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