气动人工肌肉的模糊小波神经网络控制  

Fuzzy Wavelet Neural Network Control for Pneumatic Artificial Muscle

作　　者：昝鹏[1] 颜国正[1] 黄标[1] 于莲芝[1] 

机构地区：[1]上海交通大学电子信息与电气工程学院820所,上海200240

出　　处：《系统仿真学报》2007年第23期5566-5569,共4页Journal of System Simulation

基　　金：国家自然科学基金资助项目(30570485);国家863计划资助项目(2004AA404013)

摘　　要：针对一种应用于医疗机器人领域的三自由度人工肌肉的非线性特性,结合模糊理论与小波神经网络,提出一种模糊小波神经网络控制器对人工肌肉驱动器进行控制。利用模糊小波神经网络的学习能力,采用梯度法搜寻控制器的最优参数。将采用模糊小波神经网络控制器与采用小波神经网络控制器及模糊神经网络控制器的控制系统仿真结果进行比较。仿真结果说明模糊小波神经网络控制器有效地改善了驱动器的静动态特性,具有更快的训练速度和更好的控制效果,是一种理想的气动人工肌肉控制方法。A 3-DOF artificial muscle is used in the fields of medical robots. To counteract the defects of its non-linearity, a FWNN （fuzzy wavelet neural network） was proposed for actuator control with the integration of fuzzy theory and WNN （wavelet neural network）, Using gradient method the learning of fuzzy WNN was performed to find optimal values of the parameters of controller, Result of simulation of control system based on fuzzy WNN was compared with the simulation result of control systems based on WNN and FNN （fuzzy neural network） controller. Simulation results demonstrate FWNN controller improves the static and dynamic performance of the actuator effectively. The training of system is faster and it has better control performance than others, FWNN control is a rather ideal method for this application.

关 键 词：模糊 小波神经网络 人工肌肉 控制 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP27[自动化与计算机技术—控制科学与工程]