工程力学 ›› 2018, Vol. 35 ›› Issue (10): 47-55.doi: 10.6052/j.issn.1000-4750.2017.06.0453

• 土木工程学科 • 上一篇    下一篇

基于保性能自适应RBF神经网络的MR半主动非线性鲁棒分散控制

潘兆东1, 谭平2, 周福霖2,3   

  1. 1. 东莞理工学院建筑工程系, 东莞 523808;
    2. 广州大学工程抗震研究中心, 广州 510405;
    3. 湖南大学土木工程学院, 长沙 410082
  • 收稿日期:2017-06-10 修回日期:2018-04-04 出版日期:2018-10-12 发布日期:2018-10-12
  • 通讯作者: 谭平(1973-),男,湖南人,教授,博士,主要从事结构抗震、减隔震研究(E-mail:ptan@gzhu.edu.cn). E-mail:ptan@gzhu.edu.cn
  • 作者简介:潘兆东(1986-),男,陕西人,博士,主要从事工程结构减震控制研究(E-mail:pzd0101@126.com);周福霖(1939-),男,广东人,教授,硕士,中国工程院院士,主要从事结构抗震与减震方面的研究(E-mail:zhoufl@cae.cn).
  • 基金资助:
    科技部“十二五”支撑计划子课题(2012BAJ07B02);国家自然科学基金项目(97315301-07,51408142);教育部创新团队项目(IRT13057)

SEMI ACTIVE NONLINEAR ROBUST DECENTRALIZED CONTROL BASED ON GUARANTEED PERFORMANCE ADAPTIVE RBF NEURAL NETWORK

PAN Zhao-dong1, TAN Ping2, ZHOU Fu-lin2,3   

  1. 1. Department Civil Engineering, Dongguan University of Technology, Dongguan 523808, China;
    2. Earthquake Engineering Research & Test Center, Guangzhou University, Guangzhou 510405, China;
    3. College of Civil Engineering, Hunan University, Changsha 410082, China
  • Received:2017-06-10 Revised:2018-04-04 Online:2018-10-12 Published:2018-10-12

摘要: 该文针对模型参数不确定的非线性结构半主动分散控制问题进行研究。首先,采用退化Bouc-Wen滞回模型模拟层间恢复力,并考虑模型参数(质量、刚度和阻尼)不确定及子系统间的耦合项,建立了子控制系统误差状态方程;在此基础上,设计了由保性能控制项和自适应逼近控制项构成的子控制器,其中,保性能控制项通过求解转化为线性矩阵不等式的保性能控制问题得到,逼近控制项通过RBF神经网络自适应控制律确定,同时利用Lyapunov稳定性理论对其稳定性及权值有界性进行证明;从而建立了适用于不确定结构非线性振动控制的保性能自适应RBF神经网络鲁棒分散控制(GCARBF)算法。最后,对一8层非线性结构进行MR半主动分散控制设计及0.3 g~0.8 g地震下仿真分析,结果表明了所提算法的有效性与优越性。

关键词: MR半主动控制, 鲁棒分散控制, 自适应RBF神经网络控制, 保性能控制, Lyapunov稳定性理论, 线性矩阵不等式方法

Abstract: The semi active decentralized control of nonlinear structures with uncertain parameters is studied. Firstly, the degenerated Bouc-Wen hysteretic model is utilized to simulate the restoring forces, and the error state equation of a sub-control system is established by considering the uncertainty of the model parameters (mass, stiffness and damping) and the coupling between subsystems. Secondly, a sub-controller is designed which composes of a guaranteed cost control term and an adaptive approximation control term. The guaranteed cost control term is obtained by solving the guaranteed cost control problem which is transformed into a linear matrix inequality. The approximation control term is determined by the adaptive control law of RBF neural network, and its stability and boundedness of the weights are proved by Lyapunov stability theory. And then a guaranteed cost adaptive RBF neural network robust decentralized control (GCARBF) algorithm for nonlinear vibration control of uncertain structures is established. A nonlinear 8-story building is selected as a numerical example to evaluate the control performances of the proposed algorithm. The MR semi active decentralized control design and the simulation analysis of 0.3 g~0.8 g intensity are carried out. Numerical simulation results indicate the effectiveness and superiority of the proposed algorithm.

Key words: MR semi-active control, robust decentralized control, adaptive RBF neural network control, guaranteed cost control, Lyapunov stability theory, linear matrix inequality method

中图分类号: 

  • TU352.1+1
[1] 席裕庚. 动态大系统方法导论[M]. 北京:国防工业出版社, 1988:3-5. Xi Yugeng. Introduction of large scale dynamic systems[M]. Beijing:National Defense of Industry Press, 1988:3-5. (in Chinese)
[2] Lynch J P, Law K H. Decentralized control techniques for large-scale civil structural systems[C]//Proc. of the 20th Int. Modal Analysis Conference (IMAC XX). Los Angeles. Bellingham:Society of Photo-Optical Instrumentation Engineers, 2002.
[3] Xu B, Wu Z S, Yokoyama K. Neural networks for decentralized control of cable-stayed bridge[J]. Journal of Bridge Engineering, 2003, 8(4):229-236.
[4] Rofooei F R, Monajemi-Nezhad S. Decentralized control of tall buildings[J]. The Structural Design of Tall and Special Buildings, 2006, 15(2):153-170.
[5] Monajemi -Nezhad S, Rofooei F R. Decentralized sliding mode control of multistory buildings[J]. The Structural Design of Tall and Special Buildings, 2007, 16(2):181-204.
[6] Loh C H, Chang C M. Application of centralized and decentralized control to building structure:analytical study[J]. Journal of Engineering Mechanics, 2008, 134(11):970-982.
[7] 李宏男, 李瀛, 李钢. 地震作用下建筑结构的分散控制研究[J]. 土木工程学报, 2008, 41(9):27-33. Li Hongnan, Li Ying, Li Gang. Decentralized control of structures under earthquakes[J]. China Civil Engineering Journal, 2008, 41(9):27-33. (in Chinese)
[8] Wang Y. Wireless sensing and decentralized control for civil structures:theory and implementation[D]. Stanford, California:Stanford University, 2007.
[9] Wang Y, Lynch J P, Law K H. Decentralized H controller design for large-scale civil structures[J]. Earthquake Engineering & Structural Dynamics, 2009, 38(3):377-401.
[10] 蒋扬, 周星德, 王玉. 建筑结构鲁棒分散控制方法研究[J]. 振动与冲击, 2012, 31(6):37-41. Jang Yang, Zhou Xingde, Wang Yu. A robust decentranzed control method for architectural structures[J]. Journal of Vibration and Shock, 2012, 31(6):37-41. (in Chinese)
[11] 雷鹰, 伍德挺, 刘中华. 一种适用于大型工程结构的分散振动控制方法[J]. 振动工程学报, 2012, 25(4):411-417. Lei Ying, Wu Deting, Liu Zhonghua. A decentralized vibration control algorithm for large-scale engineering structures[J]. Journal of Vibration Engineering, 2012, 25(4):411-417. (in Chinese)
[12] 汪权, 王建国, 裴阳阳. 地震作用下高层建筑结构的分散模糊迭代学习控制研究[J]. 计算力学学报, 2012, 29(5):681-686. Wang Quan, Wang Jianguo, Pei Yangyang. Decentralized fuzzy iterative learning control of tall buildings under earthquakes[J]. Chinese Journal of Computational Mechanics, 2012, 29(5):681-686. (in Chinese)
[13] 潘兆东, 谭平, 周福霖. 大型结构小增益分散稳定化容错控制研究[J]. 工程力学, 2017, 34(6):128-136. Pan Zhaodong, Tan Ping, Zhou Fulin. Decentralized stable fault-tolerant control for large-scale structure[J]. Engineering Mechanics, 2017, 34(6):128-136. (in Chinese)
[14] Yu Y, Li L, Leng X, et al. A wireless decentralized control experimental platform for vibration control of civil structures[J]. Smart Structures and Systems, 2017, 19(1):47-56.
[15] Ma T W, Xu N S, Tang Y. Decentralized robust control of building structures under seismic excitations[J]. Earthquake Engineering & Structural Dynamics, 2008, 37(1):121-140.
[16] 孙万泉, 李庆斌. 基于LMI的高层建筑结构分散H2/H鲁棒控制[J]. 地震工程与工程振动, 2007, 27(6):218-222. Sun Wanquan, Li Qingbin. Decentralized H2/H robust control for large-scale building structure based on linear-matrix inequalities (LMI)[J]. Journal of Earthquake Engineering and Engineering Vibration, 2007, 27(6):218-222. (in Chinese)
[17] Li H, Wang J, Song G, et al. An input-to-state stabilizing control approach for non-linear structures under strong ground motions[J]. Structural Control & Health Monitoring, 2011, 18(2):227-240.
[18] 潘兆东, 谭平, 周福霖. 大型结构分散控制系统的优化研究[J]. 工程力学, 2017, 34(1):154-162. Pan Zhaodong, Tan Ping, Zhou Fulin. Study on optimization of large-scale structural decentralized control[J]. Engineering Mechanics, 2017, 34(1):154-162. (in Chinese)
[19] Baber T T, Wen Y K. Random vibration hysteretic, degrading systems[J]. Journal of the Engineering Mechanics Division, 1981, 107(6):1069-1087.
[20] 刘金琨. 智能控制[M]. 第3版. 北京:电子工业出版社, 2014:132-133. Liu Jinkun. Intelligent control[M]. 3rd ed. Beijing:Electronics Industry Press, 2014:132-133. (in Chinese)
[21] 俞立. 鲁棒控制:线性矩阵不等式处理方法[M]. 北京:淸华大学出版社, 2002:8-9, 87-88. Yu Li. Robust control:linear matrix inequality approach[M]. Beijing:Tsinghua University Press, 2002:8-9, 87-88. (in Chinese)
[22] Yang J N, Wu J C, Agrawal A K. Sliding mode control for nonlinear and hysteretic structures[J]. Journal of Engineering Mechanics, 1995, 121(12):1330-1339.
[23] Dyke S J. Acceleration feedback control strategies for active and semi-active control systems:modeling, algorithm development and experimental verification[D]. USA:Dissertation of University of Notre Dame, 1996:175-186.
[24] Yi F, Dyke S J, Caicedo J M, et al. Experimental verification of multi-input seismic control strategies for smart dampers[J]. Journal of Engineering Mechanics, 2001, 27(11):1152-1164.
[1] 潘兆东, 谭平, 周福霖. 不确定结构输出反馈H保性能鲁棒分散控制研究[J]. 工程力学, 2018, 35(4): 160-167.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!
X

近日,本刊多次接到来电,称有不法网站冒充《工程力学》杂志官网,并向投稿人收取高额费用。在此,我们郑重申明:

1.《工程力学》官方网站是本刊唯一的投稿渠道(原网站已停用),《工程力学》所有刊载论文必须经本刊官方网站的在线投稿审稿系统完成评审。我们不接受邮件投稿,也不通过任何中介或编辑收费组稿。

2.《工程力学》在稿件符合投稿条件并接收后会发出接收通知,请作者在接到版面费或审稿费通知时,仔细检查收款人是否为“《工程力学》杂志社”,千万不要汇款给任何的个人账号。请广大读者、作者相互转告,广为宣传!如有疑问,请来电咨询:010-62788648。

感谢大家多年来对《工程力学》的支持与厚爱,欢迎继续关注我们!

《工程力学》杂志社

2018年11月15日