文档介绍：非最小相位系统PI/PD控制器的优化设计
摘要
非最小相位系统的右半平面存在零点或极点,本文只论述有零点的情况,如何抑制非最小相位系统右半平面零点所造成的负调至今仍是一个开放的问题。比例-积分-微分(PID)控制是在工业过程控制中最常见的一种控制算法。由于PID控制算法简单、在实际中容易被理解和实现,因此它被广泛应用于化工、冶金、机械、热工和轻工等工业过程控制系统中,许多先进控制技术都是以PID控制为基础的。但PID参数的整定一般需要经验丰富的工程技术人员来完成,使PID参数的整定有一定的难度,致使许多PID控制器没能整定的很好,因此研究自整定PID控制具有重要意义。粒子群优化算法是一类全局随机进化算法,算法通过粒子间的相互作用发现复杂搜索空间中的最优区域,它的优势在于简单易行而且功能强大。本文根据粒子群算法具有对整个参数空间进行高效并行搜索的特点,提出一种对PID控制器参数和非最小相位系统的两阶段PI/PD控制器参数进行自整定的计算框架。仿真结果表明了所提出的算法与基于遗传算法的PID控制器相比具有较快的调节时间,较小超调和负调。
关键词:非最小相位系统;粒子群算法;PID控制;自整定
Optimization Design of PI / PD Controller for Non-minimum Phase Systems
Abstract
Non-minimum phase (NMP) systems have right half-plane zeros or poles, but we only discuss the NMP system having zeros in this paper. How to restrain the negative transfer caused by the right half-plane zeros of the NMP systems is still an open question. Proportional-integral-derivative (PID) controller in the industrial process control is one of the most general control methods. Since PID controller is simple and easily understood and realized, which has been widely used in chemical industry, metallurgy, mechanical, thermal and light industrial process control system. But to tune parameters of PID controller needs rich experience of engineering and technical workers. Moreover, because the actual system is different and has lagged behind, nonlinear and other factors, many PID controllers could not be settled in a very good manner. The research on the self-tuning of PID control parameters is of great significance. Particle swarm optimization (PSO) is a global stochastic evolutionary algorithm. It tries to find optimal regions plex searching space through the interaction of particles in the population. The predominance of the algorithm is its excellent performance and simple implement. In this paper, a two-stage PI/PD controller is investigated on the basis of PSO algorithm to decrease peak overshoot, undershoot, settling time and rise time of non-minimum phase (NMP) system simultaneously. N