基于离散模糊PI控制和粒子群优化的控制器系统设计方法

J. Cheon, Jinwook Kim, Hongju Kim, Soonman Kwon, Youngkiu Choi
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摘要

本文提出了一种基于离散模糊PI控制和粒子群优化的控制器系统设计方法。与传统的PI控制器不同,离散模糊PI控制器根据其输入变量具有可变增益。由于模糊控制器中存在大量强耦合参数,因此模糊控制器的参数整定比较复杂。在离散时域,离散模糊PI控制器是传统PI控制器的超集。利用包含关系选择模糊PI控制器的初始参数。并且,为简单起见,仅使用4条规则来构造非线性模糊控制面。利用粒子群算法对离散模糊PI控制器的整定参数进行了优化。为了验证采用离散模糊PI控制和粒子群算法设计的控制器的有效性,我们将其应用于风力发电机桨距控制器。因此,与PI控制器不同,所提出的控制器具有可变增益,并使螺距控制器在边界操作区域中工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic Design Method of Controller using Discrete Fuzzy PI Control and Particle Swarm Optimization
This paper presents a systematic design method of a controller using the discrete fuzzy PI control and the particle swarm optimization (PSO). Unlike a conventional PI controller, the discrete fuzzy PI controller has variable gains according to its input variables. Generally, it is complicated to tune the parameters of a fuzzy controller because there are too many parameters which are strongly coupled. In the discrete-time domain, the discrete fuzzy PI controller is a superset of the conventional PI controller. And the initial parameters of the fuzzy PI controller are selected by using the inclusion relationship. And, for the sake of simplicity, only four rules are used to construct a nonlinear fuzzy control surface. The tuning parameters of the discrete fuzzy PI controller are optimized by using the PSO. To verify the effectiveness of the controller designed by using the discrete fuzzy PI control and the PSO, we applied it to a wind turbine pitch controller. As a result, the proposed controller has variable gains, unlike the PI controller, and make the pitch controller operate in boarder operating regions.
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