Design and application of fuzzy immune PID adaptive control based on particle swarm optimization in thermal power plants

R. Bouchebbat, S. Gherbi
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引用次数: 4

Abstract

The PID controller is the most used controller in the industry thanks to its simplicity and satisfactory performances, unfortunately there is a class of systems that can't achieve satisfactory performances with a simple PID controller as the nonlinear and the delayed systems. These last years, it appeared a lot of innovative control techniques as the bio-inspired methods, one of the most promising of them is the immune PID controller, it is inspired by the immune system regulating mechanism known by its robustness and self-adaptability. In this paper, the immune feedback mechanism and fuzzy inference are incorporated to design a fuzzy immune PID adaptive controller while the particle swarm optimization (PSO) algorithm is used to optimize its parameters. The simulation results using a main steam temperature system as the controlled plant, verify that the strategy has strong adaptability to the transformation of the system parameters and has advantages of a good time performances and robustness ability.
基于粒子群优化的模糊免疫PID自适应控制在火电厂中的设计与应用
PID控制器由于其简单和令人满意的性能而成为工业上使用最多的控制器,不幸的是有一类系统不能用简单的PID控制器达到令人满意的性能,如非线性和时滞系统。近年来,出现了许多创新的控制技术作为仿生方法,其中最有前途的是免疫PID控制器,它的灵感来自免疫系统的调节机制,以其鲁棒性和自适应性而闻名。本文将免疫反馈机制与模糊推理相结合,设计了一种模糊免疫PID自适应控制器,并采用粒子群优化算法对其参数进行优化。以某主汽温系统为被控对象的仿真结果验证了该策略对系统参数的变换具有较强的适应性,具有较好的时效性和鲁棒性。
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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