基于粒子群优化算法的变论域模糊PID控制器在过热汽温控制中的应用

针对锅炉过热汽温大滞后和大惯性等难以建立精确的数学模型的问题,设计了模糊PID控制器。通过模糊推理对PID的参数在线调整,加入了变论域思想对控制系统进行改进,最后将粒子群优化算法应用于变论域模糊控制器中,对量化因子及PID的三个参数Kp、Ki和Kd进行优化。将模糊PID控制器应用于过热汽温度控制系统进行仿真。仿真结果表明:采用基于粒子群优化算法的变论域模糊PID控制比传统的PID控制具有较强的鲁棒性和抗干扰能力,具有明显的优越性。

Application of PSO-based Variable Universe Fuzzy PID Controller in Superheated Steam Temperature Control System

A fuzzy PID controller was designed aiming at the problem that it is difficult to establish a precise mathematical model for superheat steam temperature of boilers due to its features of large lag, great inertia, etc. Through online adjustment of PID parameters by fuzzy reasoning, combining with the ideas of variable universe to improve the control system, and introducing the particle swarm optimization （PSO） algorithm to the variable universe fuzzy controller, the quantization factor and three parameters Kp, Ki and Kd of the PID were optimized. Simulations were conducted to the superheat steam temperature control system using the fuzzy PID controller. Results show that the PSO-based variable universe fuzzy PID control has strong robustness and anti-interference capability, which therefore is apparently superior to traditional PID control.