内分泌LQR控制策略及其主动悬架减振研究

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摘要基于生物内分泌系统激素调节机理设计了内分泌智能控制器，结合传统的线性二次型调节器（LQR），提出一种新型复合结构的内分泌LQR控制器。将其应用于汽车主动悬架减振控制，采用ADAMS/View构建麦弗逊汽车悬架模型，以典型的正弦路面输入和随机路面输入作为激励，通过MATLAB与ADAMS联合仿真对比分析了内分泌LQR控制、传统LQR控制及被动悬架的减振效果。研究结果表明，内分泌LQR控制品质优良、对变化的工况参数具较好的适应性,减振效果要优于传统LQR控制。该方法为主动悬架减振提供了一种新的控制方案，同时也为内分泌智能控制策略及其应用提供了新思路。

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	金耀1 于德介2 陈中祥1 蒋明华1 贺欣1

关键词 ：主动悬架, 内分泌系统, LQR, 智能控制, 减振控制

Abstract：By combining the traditional linear quadratic regulator (LQR) with the endocrine intelligent controller which is based on the endocrine hormone regulation principles, a new compound endocrine LQR controller is proposed. The proposed strategy is then applied to the vibration control of vehicle active suspension, in which a Mcpherson suspension mode is established in ADAMS/View. With sine and random excitations as typical road input, comparison is performed among the endocrine LQR, LQR and passive suspensions by means of the co-simulation of ADAMS and MATLAB. Simulation results demonstrate that the proposed endocrine LQR is superior to LQR, and has advantages of excellent performance, strong adaptability. The proposed control strategy not only provides a new control scheme for active suspension, but also a possible new way for endocrine intelligent control and its applications.

Key words： Active suspension Endocrine system LQR Intelligent control Vibration control

收稿日期: 2015-04-15 出版日期: 2016-05-15

引用本文:

金耀1 于德介2 陈中祥1 蒋明华1 贺欣1. 内分泌LQR控制策略及其主动悬架减振研究[J]. 振动与冲击, 2016, 35(10): 49-54.
JIN Yao1 YU Dejie2 Chen Zhongxiang1 JIANG Minghua1 He Xin1. Endocrine LQR Control Strategy and Its Application in Active Suspensions Vibration#br#. JOURNAL OF VIBRATION AND SHOCK, 2016, 35(10): 49-54.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2016/V35/I10/49

[1] Cao Dongpu, Song Xubin, Mehdi Ahmadian. Editors’ perspectives：road vehicle suspension design, dynamics, and control[J]．Vehicle System Dynamics，2011，49(1/2)：3-28.
[2] 余志生．汽车理论（第5版）[M]．北京：机械工业出版社，2009.
Yu zhisheng. Automobile Theory（5th Edition）[M]. Beijing: China Machine Press, 2009.
[3] Cao Jiangtao, Liu Honghai, Li Ping, et al. State of the art in vehicle active suspension adaptive control systems based on intelligent methodologies[J]. IEEE Transactions on Intelligent Transportation Systems，2008，9(3): 392-405.
[4] 黄晨，陈龙，袁朝春，等．半主动悬架系统的混合模糊控制[J]．汽车工程，2014，36(8)：512-517.
Huang chen, Chen Long, Yuan zhaochun, et al. Hybrid fuzzy control of semi-active suspension system[J]. Automotive Engineering, 2014，36(8)：512-517.
[5] 王威，宋玉玲，王体春，等．非确定因素下汽车半主动悬架的智能控制[J]．工程力学，2012，29(9)：337-342.
Wang Wei, Song Yu-ling, Wang Ti-chun, et al. Intelligent control of automotive semi-active suspension with uncertain factors[J]. Engineering mechanics，2012，29(9)：337-342.
[6] Yu Miao, Dong XiaoMin, Choi S B, et al. Human simulated intelligent control of vehicle suspension system with MR dampers[J]. Journal of Sound and Vibration，2009，319(3/5)：753-767.
[7] Mendao M. A neuro-endocrine control architecture applied to mobile robotics[D]. Canterbury，UK，University of Kent，2007.
[8] Xu Qingzheng, Wang Lei. Recent advances in the artificial endocrine system[J]. Journal of Zhejiang University(Science C), 2011, 12(3): 171-183.
[9] 顾文斌，唐敦兵，郑堃，等. 基于激素调节机制改进型自适应粒子群算法在置换流水车间调度中的应用研究[J]. 机械工程学报，2012，48(14): 177-182.
Gu Wenbin, Tang dunbing, Zeng Kun, et al. Research on permutation flow-shop scheduling problem based on improved adaptive particle swarm optimization algorithm with hormone modulation mechanism[J]. China Journal of Mechanical Engineering，2012，48(14): 177-182.
[10] 刘宝, 丁永生. 一种基于睾丸素分泌调节原理的双层结构控制器[J].上海交通大学学报, 2006, 40(5): 822-824.
Liu Bao, Ding Yongsheng. A two-level controller based on the modulation principle of testosterone release[J]. Journal of Shanghai Jiaotong University，2006, 40(5): 822-824.
[11] Ding Yongsheng, Xiao Liang, Hao Kuangrong,et al. An intelligent cooperative decoupling controller for coagulation bath in polyacrylonitrile carbon fiber production[J]. IEEE Transactions on Control Systems Technology，2013，21(2)：467-479.
[12] 王磊，徐庆征. 基于晶格的人工内分泌系统模型及在多机器人系统中的应用[J]. 中国科学(信息科学)，2011，41(5): 562-579.
Wang Lei, Xu Qingzheng. Lattice-based artificial endocrine system model and its application in robotic swarms[J]. Science China (Information Sciences)，2011，41(5): 562-579.
[13] Tilbrook A J, Clarke I J. Neuroendocrine mechanisms of innate states of attenuated responsiveness of the hypothalamo-pituitary adrenal axis to stress[J]. Frontiers in Neuroendocrinology，2006，27(3)：285-307.
[14] 金耀，于德介，宋晓琳. 主动悬架的一种基于状态反馈的单神经元多变量控制策略[J].振动与冲击，2008，27(8): 12-15.
Jin Yao, Yu Dejie, Song xiaoLin. Single neuron multivariables control strategy for active suspensions based on state feedback[J]. Journal of Vibration and Shock，2007，27(8)：12-15.
[15] 喻凡，林逸．汽车系统动力学[M]．北京：机械工业出版社，2005.
Yu Fan, Lin Yi. Vehicle System Dynamics[M]. Beijing: China Machine Press, 2005.