摘要
干扰观测器(DOB)是一种解决控制系统低速非线性的有效手段,其补偿效果取决于名义模型的精度,传统的、结合系统频谱特性的、通过试凑的方法得来的近似模型难以达到理想的控制效果。该文在建立系统控制模型的基础上,研究了粒子群(PSO)算法,对算法进行了改进以避免其陷入局部极小,同时提高了其收敛精度。基于改进算法对转台参数进行辨识,在此基础上,设计了干扰观测器。仿真结果表明,基于此方法设计的干扰观测器应用于控制系统中可以得到很好的补偿效果。
Disturbance observer（DOB） is a kind of control system of low-speed nonlinear effective means to solve,the compensation effect depending on the accuracy of the nominal model,traditional combined with the spectrum charac- teristics of the system by trial and error method to approximate model is difficult to achieve the ideal control effect. In this paper,based on the system control model,the particle swarm optimization（PSO）algorithm is studied ,and the algorithm is improved to avoid the local minimum,and the convergence accuracy is improved. Based on the im- proved algorithm,the parameters of the turntable are identified,and the disturbance observer is designed. The simula- tion results show that the model has high precision. The disturbance observer based on this method can be used in the control system to get better compensation effect.
出处
《自动化与仪表》
2016年第9期1-4,52,共5页
Automation & Instrumentation
关键词
转台
PSO算法
干扰观测器
低速非线性
turntable
particle swarm optimization （PSO） algorithm
disturbance observer （DOB）
low speed nonlinear
