气动人工肌肉的模糊小波神经网络控制被引量：7

Fuzzy Wavelet Neural Network Control for Pneumatic Artificial Muscle

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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.

作者昝鹏颜国正黄标于莲芝

机构地区上海交通大学电子信息与电气工程学院

出处《系统仿真学报》 EI CAS CSCD 北大核心 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)

关键词模糊小波神经网络人工肌肉控制 fuzzy wavelet neural network artificial muscle control

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—检测技术与自动化装置]

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参考文献12

1Tondu B, Ippolito S, Guiochet J. A Seven-degrees-of-freedom Robot-arm Driven by Pneumatic Artificial Muscles for Humanoid Robots [J]. The International Journal of Robotics Research (S0278-3649), 2005,24(4): 257-274.
2Koichi S, Shoichi L, Hirohisa T. Development of Flexible Microactuator and Its Applications to Robotic Mechanisms [C]// Proceedings of the 1991 IEEE International Conference on Robotics and Automation. Washington, USA: IEEE, 1991, 4(2): 1622-1627.
3Gelenn K K, Joseph M C, Blake H. Artificial muscles: Actuators for Biorobotic Systems[J]. The international Journal of robotics research (S0278-3649), 2002, 21(4): 295-309.
4Deng W, Zhang H G. Fuzzy Neural Networks Adaptive Control of Micro Gas Turbine with Prediction Model [C]// Proceedings of the 2006 IEEE International Conference on Networking, Sensing and Control. Ft. Lauderdale, Florida, USA: IEEE, 2006,1053-1058.
5Lin F J, Shieh H J, Huang P K. Adaptive Wavelet Neural Network Control With Hysteresis Estimation for Piezo-positioning Mechanism [J]. IEEE Transactions on Neural Networks (S1045-9227), 2006, 2(17): 432-444.
6E1-Rabaie N M, Awad H A, Mahmoud T A. Wavelet fuzzy neural network-based predictive control system [C]// Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference, Dubrovnik, Croatia, IEEE, 2004,1(12): 307-310.
7孙炜,王耀南.模糊小波基神经网络的机器人轨迹跟踪控制[J].控制理论与应用,2003,20(1):49-53. 被引量：22
8谭永红党选举梁峰.基于动态小波神经网络的非线性动态系统辨识.系统仿真学报,2001,13:51-55.
9朱娟萍,侯忠生.神经网络模糊非参数模型自适应控制及仿真[J].系统仿真学报,2006,18(6):1623-1625. 被引量：1
10胡玉玲,曹建国.基于模糊神经网络的动态非线性系统辨识研究[J].系统仿真学报,2007,19(3):560-562. 被引量：23

二级参考文献20

1徐春梅,尔联洁,刘金琨.动态模糊神经网络及其快速自调整学习算法[J].控制与决策,2005,20(2):226-229. 被引量：16
2李友善,班喜光.Fuzzy控制理论在甜菜制糖过程的应用[J].自动化学报,1994,20(3):334-337. 被引量：16
3侯忠生．非参数模型及其自适应控制理论[M]．北京：科学出版社，1998．
4Lin C J, Lin C T. An ART-Based Fuzzy Adaptive Learning Control Networks [I]. IEEE Traas on Fuzzy Systems, 1997, 5(4): 477-496.
5Meng J E, Jun L, Jianya L, Maolin N. A Novel Development Tool of Fuzzy Neural Networks [J]. American Control Conference. 2000 (4):2458-2462.
6SLOTINE J J E, LI W. On the adaptive control of robot manipulators [J] . Int J of Robotics Research, 1989,6(3) :49 - 59.
7HANM C, QU Z. A new nonlinear learning control for robotic manipulators [ J]. Advanced Robotics, 1996,10( 1 ): 1 - 15.
8QU Z, DAWSON D. Robust Tracking Control of Robot Manipulators[M]. New York: IEEE Press, 1996.
9ZHANG Qinghua. Using wavelet network in nonparametric estimation[J]. IEEE Trans on Neural Networks, 1997,8(2) :227 - 236.
10REYNERI M L. Unification of neural and wavelet networks and fuzzy systems [J]. IEEE Trans on Neural Networks, 1999,10(4):801 - 814.