摘要
CVT电液伺服系统在工作时,由于工作元件动力学性能的改变,造成系统的非线性和参数时变,为了降低建立系统控制模型的误差,采用最小二乘递推算法对系统参数进行辨识。提出了免疫粒子群控制算法,设计出免疫粒子群PID控制器,对最优指标和PID参数进行寻优,并将该控制方法应用于CVT电液伺服系统中。仿真结果表明,与模糊控制算法相比,基于免疫粒子群算法的CVT电液伺服系统的动态特性得到了有效的改善,提高了系统抗干扰能力以及参数时变的鲁棒性。
In order to reduce the error to establish the system control model,recursive least squares algorithm is used to identify the system parameters,when CVT electro-hydraulic servo system at work,as a result of changes in dynamic performance of working element,resulting in the nonlinear and time-varying parameters. The immune-particle swarm control algorithm is proposed,designing immune-particle swarm PID controller,optimizing optimal index and PID parameters,and using this method in CVT electro-hydraulic servo system. The simulation result has indicated that the CVT electro-hydraulic servo system＇s dynamic characteristic compared with fuzzy control system has improved effectively which based on immune-particle swarm algorithm,sharpened the system＇s anti-interference ability as well as parameter time-variance robustness.
出处
《现代制造工程》
CSCD
北大核心
2014年第7期103-108,共6页
Modern Manufacturing Engineering
基金
安徽省高校自然科学基金资助项目(KJ2013B159)
巢湖学院自然科学基金资助项目(XLY-201206)
关键词
CVT
电液伺服系统
最小二乘递推算法
免疫粒子群算法
CVT
electro-hydraulic servo system
recursive least squares algorithm
immune-particle swarm algorithm
