[1]付兴建,郭宏梅.小脑神经网络用于不确定时滞系统的鲁棒非脆弱控制[J].西安科技大学学报,2020,(03):477-483.[doi:10.13800/j.cnki.xakjdxxb.2020.0314]
 FU Xing-jian,GUO Hong-mei.Application of CMAC to robust non-fragile control of systems with time-delay and uncertainties[J].Journal of Xi'an University of Science and Technology,2020,(03):477-483.[doi:10.13800/j.cnki.xakjdxxb.2020.0314]
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小脑神经网络用于不确定时滞系统的鲁棒非脆弱控制(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2020年03期
页码:
477-483
栏目:
出版日期:
2020-05-15

文章信息/Info

Title:
Application of CMAC to robust non-fragile control of systems with time-delay and uncertainties
文章编号:
1672-9315(2020)03-0477-07
作者:
付兴建郭宏梅
(北京信息科技大学 自动化学院,北京 100192)
Author(s):
FU Xing-jianGUO Hong-mei
(School of Automation,Information Science and Technology University,Beijing 100192,China)
关键词:
小脑模型神经网络 非脆弱控制 不确定性 时滞 线性矩阵不等式
Keywords:
cerebellar model articulation controller non-fragile control uncertainty time-delay linear matrix inequality
分类号:
TP 273
DOI:
10.13800/j.cnki.xakjdxxb.2020.0314
文献标志码:
A
摘要:
针对不确定时滞系统的鲁棒跟踪控制问题,设计了一种基于小脑神经网络CMAC的鲁棒非脆弱控制器。首先,给出小脑模型神经网络控制系统的算法。其次针对一类不确定时滞系统,根据李雅普诺夫稳定理论,进行了鲁棒非脆弱控制器的设计。假设反馈控制中即含有状态反馈不确定性,也具有状态时滞的不确定性。证明不确定时滞系统鲁棒非脆弱控制存在的条件。该条件可以利用Matlab的线性矩阵不等式LMI工具箱来求解鲁棒控制器的参数。之后利用CMAC神经网络较强的学习能力和鲁棒非脆弱控制器对参数摄动抑制作用的特点,将鲁棒非脆弱控制器与小脑模型神经网络CMAC相结合,构成小脑模型神经网络与鲁棒非脆弱控制器的复合控制,实现对不确定时滞系统的跟踪控制。仿真结果显示,对于输入端扰动和一定程度的参数摄动,经过复合控制器的作用,被控系统能在短时间的抖动后逐渐趋于稳定,不仅具有较快的响应速度,还具有较短的收敛时间和令人满意的跟踪精度。该种复合控制表现出较强抗干扰能力及鲁棒性。
Abstract:
The robust non-fragile controller based on CMAC neural network was designed for the tracking control problem of uncertain time-delay systems.Firstly,the algorithm of the cerebellar model neural network control system was put forward.Secondly,the tracking control problem was transformed into a robust control problem.For a class of uncertain time-delay systems,the robust non-fragile controller was designed according to Lyapunov stability theory.It was assumed that the feedback control contained state feedback uncertainty and uncertainty of state delay feedback.The conditions for the existence of a robust non-fragile controller were proved.It was possible to solve the parameters of the robust controller by using the linear matrix inequality LMI toolbox in Matlab.Then,by using the CMAC neural network with strong learning ability and the characteristics of robust non-fragile controller for parameter perturbation suppression,the two controllers were combined to form the composite control of the cerebellar model neural network and the robust non-fragile controller.Tracking control for uncertain time-delay systems was realized.The simulation results show that for the input disturbance and a certain degree of parameter perturbation,the controlled system can be gradually stabilized after a short period.Through the composite controller,the system has a faster response speed,a shorter convergence time and satisfactory tracking accuracy.This kind of composite control shows strong anti-interference ability and robustness.

参考文献/References:

[1] Albus J S.Data storage in the cerebellar model articulation controller[J].Journal of Dynamic Syststem,Measurement and Control,1975,97(3):228-233. [2]张 强,于宏亮,许德智.基于自组织小波小脑模型关节控制器的不确定非线性系统鲁棒自适应终端滑模控制[J].控制理论与应用,2016,33(3):387-397. ZHANG Qiang,YU Hong-liang,XU De-zhi.Robust adaptive terminal sliding mode control for uncertain nonlinear systems based on self-organizing wavelet cerebellar model joint controller[J].Control Theory and Applications,2016,33(3):387-397. [3]Chih-Min Lin,Hsin-Yi Li.TSK fuzzy CMAC-based robust adaptive backstepping control for uncertain nonlinear systems[J].IEEE Transactions on Fuzzy Systems,2012,20(6):1147-1154. [4]Ngo T Q,Phuong T V.Robust adaptive self-organizing wavelet fuzzy CMAC tracking control for deicing robot manipulator[J].International Journal of Computers Communications & Control,2015,10(4):567-578. [5]屈百达,徐培培.不确定线性时变时滞系统的非脆弱鲁棒H控制器设计[J].计算机工程与应用,2015,51(10):43-46. QU Bai-da,XU Pei-pei.Design of non-fragile robust H controller for uncertain linear time-varying delay systems[J].Computer Engineering and Applications,2015,51(10):43-46. [6]Hamdy M,Hamdan I.Non-fragile controller design for a class of multivariable bilinear systems[J].IMA Journal of Mathematical Control and Information,2016,33(2):441-455. [7]卢军锋,吴钟鸣,向峥嵘.非线性切换系统鲁棒非脆弱控制器设计与仿真[J].计算机测量与控制,2013,21(9):2464-2467. LU Jun-feng,WU Zhong-ming,XIANG Zheng-rong.Design and simulation of robust non-fragile controller for nonlinear switched systems[J].Computer Measurement and Control,2013,21(9):2464-2467. [8]刘 艳,姜 顺,潘 丰.网络化控制系统的非脆弱耗散控制[J].控制工程,2018,25(2):245-252. LIU Yan,JIANG Shun,PAN Feng.Non-fragile dissipation control of networked control systems[J].Control Engineering,2018,25(2):245-252. [9]马 克,米 林,谭 伟.主动悬架非脆弱H控制器设计[J].重庆理工大学学报(自然科学版),2017(12):15-21. MA Ke,MI Lin,TAN Wei.Design of non-fragile H controller for active suspension[J].Journal of Chong-qing University of Technology(Natural Science),2017(12):15-21. [10]Faraji-Niri M.Robust non-fragile asynchronous controller design for continuous-time markov jump linear systems:non-homogeneous markov process approach[J].Circuits Systems & Signal Processing,2018,37(3):1-22. [11]Kim J H.Delay-dependent robust and non-fragile guaranteed of cost control for uncertain singular systems with time-varying state and input delays[J].International Journal of Control Automation and Systems,2009,7(3):357-364. [12]WO Song-lin,LIU Feng,ZOU Yun.Non-fragile decentralized H controller design for singular large-scale systems[J].Control and Decision,2012,27(4):487-492. [13]代慧芳.不确定中立时滞系统的非脆弱H控制器[J].控制工程,2017,24(3):655-660. DAI Hui-fang.Non-fragile H controller for uncertain neutral delay systems[J].Control Engineering,2017,24(3):655-660. [14]吴玉彬,张合新,朱开锐.火箭发动机燃烧过程的鲁棒非脆弱H控制[J].爆炸与冲击,2019(3):98-109. WU Yu-bin,ZHANG He-xin,ZHU Kai-rui.Robust non-fragile H control for rocket engine combustion process[J].Explosion and Shock Waves,2019(3):98-109. [15]程昊宇,董朝阳,王 青,等.变体飞行器的非脆弱有限时间鲁棒控制器设计[J].控制与决策,2017,32(11):1933-1940. CHENG Hao-yu,DONG Chao-yang,WANG Qing,et al.Non-fragile finite-time robust controller design for variant aircraft[J].Control and Decision,2017,32(11):1933-1940. [16]Fu S,Qiu J,Ji W.Non-fragile control of fuzzy affine dynamic systems via piecewise Lyapunov functions[J].Frontiers of Computer Science,2017,11(6):1-11. [17]李红霞,黄已芯,田水承,等.小脑神经网络在矿工疲劳监测控制系统中的应用[J].西安科技大学学报,2018,38(3):443-451. LI Hong-xia,HUANG Yi-xin,TIAN Shui-cheng,et al.Miner fatigue monitoring and control system based on Cerebellar Model Articulation Controller neutral network[J].Journal of Xi'an University of Science and Technology,2018,38(3):443-451. [18]WEN Chun-ming,CHENG Ming-yang.Development of a recurrent fuzzy CMAC with adjustable input space quantization and self-tuning learning rate for control of a dual-axis piezoelectric actuated micromotion stage[J].IEEE Transactions on Industrial Electronics,2013,60(11):5105-5115. [19]Lin C M,Li H Y.Intelligent control using the wavelet fuzzy CMAC backstepping control system for two-axis linear piezoelectric ceramic motor drive systems[J].IEEE Transactions on Fuzzy Systems,2014,22(4):791-802. [20]Jain D,Mehta S,Gandhi K,et al.Comparison of intubation conditions with CMAC Miller video scope and conventional Miller laryngoscope in lateral position in infants:a prospective randomized trial[J].Pediatric Anesthesia,2018,28(3):226-236. [21]Angerman S,Kirves H,Nurmi J.A before-and-after observational study of a protocol for use of the CMAC video with a Frova introducer in rapid sequence intubation[J].Anesthesia,2018,12(1):47-59. [22]朱大奇,张 伟.基于平衡学习的CMAC神经网络非线性辨识算法[J].控制与决策,2004,19(12):1425-1428. ZHU Da-qi,ZHANG Wei.Nonlinear identification algorithm for CMAC neural networks based on balanced learning[J].Control and Decision,2004,19(12):1425-1428. [23]裴建军,王宏文.驱动平面机械手的液压系统建模及CMAC-PID控制研究[J].中国工程机械学报,2018,16(3):41-46. QI Jian-jun,WANG Hong-wen.Hydraulic system modeling and CMAC-PID control of driving plane manipulator[J].Chinese Journal of Construction Machinery,2018,16(3):41-46. [24]孟凡亮,王志胜.基于CMAC的电动负载模拟器的研究[J].机械与电子,2018,36(5):25-28. MENG Fan-liang,WANG Zhi-sheng.Research on electric load simulator based on CMAC[J].Mechanics & Electronics,2018,36(5):25-28. [25]Nam KyuKwon,Seok Park,PooGyeon Park.H control for singular Markovian jump systems with incomplete knowledge of transition probabilities[J].Applied Mathematics and Computation,2017,295:126-135.

备注/Memo

备注/Memo:
收稿日期:2020-01-03 责任编辑:高 佳
基金项目:国家自然科学基金(61573230); 北京信息科技大学促进高校内涵发展科研水平提高项目(5211910950); 北京市教委科技计划项目(KM201811232013)
通信作者:付兴建(1974-),男,山东聊城人,博士,副教授,E-mail:redbrook@163.com
更新日期/Last Update: 2020-05-15