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基于粒子群优化的时间响应相似性对不确定区间系统进行数字重新设计。

Digital redesign of uncertain interval systems based on time-response resemblance via particle swarm optimization.

作者信息

Hsu Chen-Chien, Lin Geng-Yu

机构信息

Department of Electrical Engineering, Tamkang University, Tamsui, Taipei County, Taiwan.

出版信息

ISA Trans. 2009 Jul;48(3):264-72. doi: 10.1016/j.isatra.2009.01.008. Epub 2009 Feb 28.

Abstract

In this paper, a particle swarm optimization (PSO) based approach is proposed to derive an optimal digital controller for redesigned digital systems having an interval plant based on time-response resemblance of the closed-loop systems. Because of difficulties in obtaining time-response envelopes for interval systems, the design problem is formulated as an optimization problem of a cost function in terms of aggregated deviation between the step responses corresponding to extremal energies of the redesigned digital system and those of their continuous counterpart. A proposed evolutionary framework incorporating three PSOs is subsequently presented to minimize the cost function to derive an optimal set of parameters for the digital controller, so that step response sequences corresponding to the extremal sequence energy of the redesigned digital system suitably approximate those of their continuous counterpart under the perturbation of the uncertain plant parameters. Computer simulations have shown that redesigned digital systems incorporating the PSO-derived digital controllers have better system performance than those using conventional open-loop discretization methods.

摘要

本文提出了一种基于粒子群优化(PSO)的方法,用于为基于闭环系统时间响应相似性的具有区间对象的重新设计数字系统推导最优数字控制器。由于难以获得区间系统的时间响应包络,该设计问题被表述为一个成本函数的优化问题,该成本函数基于重新设计数字系统的极值能量对应的阶跃响应与连续对应系统的阶跃响应之间的聚合偏差。随后提出了一个包含三个粒子群优化算法的进化框架,以最小化成本函数,从而为数字控制器推导一组最优参数,使得在不确定对象参数的扰动下,重新设计数字系统的极值序列能量对应的阶跃响应序列能够适当地逼近其连续对应系统的阶跃响应序列。计算机仿真表明,采用基于粒子群优化算法推导的数字控制器的重新设计数字系统比使用传统开环离散化方法的系统具有更好的系统性能。

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