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基于NSGA_2与LMI的主动悬架混合H_2/H_∞鲁棒控制 被引量:1

Investigation on Active Suspension Mixed H_2/H_∞ Robust Control Based on NSGA_2 and LMI
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摘要 考虑实际应用,提出一种考虑电液作动器动态特性的主动悬架模糊静态输出反馈控制器的设计方法。利用T-S模糊模型逼近具有非线性动态特性的主动悬架模型,将悬架设计考虑的三个指标中的行驶平顺性(车身垂直加速度)作为H2性能指标,操纵稳定性(轮胎动载荷)和悬架动行程作为H∞性能指标,利用多目标遗传算法——NSGA_2对控制增益进行搜索,通过解线性矩阵不等式得到H2和H∞范数。用MATLAB/Simulink仿真进行比较,结果表明,所得主动悬架的三个性能指标都优于被动悬架。 For practical application,this paper presented a fuzzy static output feedback controller design approach for vehicle electro-hydraulic active suspensions.Takagi-Sugeno(T-S) fuzzy modeling was applied for approximating the dynamic nonlinear active suspension model.Three main performance requirements should be considered in designing suspension,ride comfort,handing stability and suspension deflection,this paper took the vertical acceleration of the car body as H2 performance,and suspension deflection and tyre deflection as the H∞ performance.NSGA_2 was atilized for searching the feedback gain matrix,the H2 and H∞ norm were acquired via solving LMI.The comparison of the simulation results between active suspension and passive suspension in MATLAB/simulink shows that the three main performances of active suspension are better.
机构地区 长沙理工大学
出处 《中国机械工程》 EI CAS CSCD 北大核心 2011年第13期1634-1637,共4页 China Mechanical Engineering
关键词 T-S模糊模型 非支配排序遗传算法(NSGA_2) 线性矩阵不等式(LMI) 主动悬架 Takagi-Sugeno(T-S) fuzzy modeling elitist non-dominated sorting genetic algorithm(NSGA_2) linear matrix inequalities(LMI) active suspension
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  • 1[1]Takagi T,Sugeno M.Fuzzy identification of systems and its applications to modeling and control[J].IEEE Trans.Syst.,Man,Cybern,1985(15):116-132.
  • 2[2]Friedland B.Advanced control systems Design[M].Upper Saddle River,NJ:Prentice-Hall,1996.
  • 3[3]Sugeno M,Kang G T.Structure identification of fuzzy model[J].fuzzy sets Syst,1988(28):15-33.
  • 4[4]Sugeno M,Kang G T.Fuzzy Modeling and Control of Multilayer incinerator[J].Fuzzy sets Syst,1986(18):329-346.
  • 5[5]Tanaka K,Sano M.On the Concept of Fuzzy Regulators and Fuzzy Observers[J].Proceedings of Third IEEE International Conference of Fuzzy Systems,1994(2):767-772.
  • 6[6]Cannon R H.Dynamics of Physical Systems[M].NewYork:McGraw-Hill,1967.
  • 7Hrovat D. Survey of Advanced Suspension Developments and Related Optimal Control Applications[J]. Automatica, 1997,33(10) : 1781-1817.
  • 8Hayakawa K, Mastumoto K, Yamashita M, et al. Robust H∞ Output Feedback Control of Decoupled Automobile Active Suspension System [J]. IEEE Trans. on Automatic Control, 1999,44(2) :392-396.
  • 9Carsten W. Multiobjective H2/H∞ Control [J]. IEEE Trans. Automat. Control, 1995,40 (6) : 1054- 1062.
  • 10Gao Huijun, Lain J, Wang Changhong. Multi-- objective Control of Vehicle Active Suspension Systems via Load--dependent Controllers[J].Journal of Sound and Vibration, 2006,290, (3/5) : 654-675.

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  • 1王前宇,孙健国,李秋红.航空发动机三变量鲁棒控制器设计[J].航空动力学报,2009,24(11):2607-2611. 被引量:2
  • 2Daniel E M,Mauro R. Simultaneous stabilization with near optimal LQR performanee[J]. IEEE Transactions on Au- tomatic Control, 2001,46(10) : 1543-1555.
  • 3De Hoff R L,Hall W E. Design of a multivariable control- ler for an advanced turbofan engine[R]. Clearwater, US: 15th Conference on Decision and Control and Symposium on Adaptive Processes, 1976.
  • 4Doyle J C,Glover K, Khargonekar P P, et al. State space solution to standard H2 and H∞ control problems[J]. IEEE Transactions on Automatic Control, 1989, 34 ( 8), 831-847.
  • 5Koroglu H,Carsten W S. An LMI approach to Ha synthe- sis subject to almost asymptotic regulation constraints[J]. Systems and Control Letters, 2008,57 (4) : 300-308.
  • 6Stron R,Price K. Differential evolution:a simple and effi- cient adaptive scheme for global optimization over continu- ous spaces[R]. Berkeley: International Computer Science Institute, Technical Report TR-95-012,1995.
  • 7Deb K. Multi-objective optimization using evolutionary al- gorithms[M]. New York:John Wiley and Sons,2001.
  • 8Zitzler E, Thiele L. Multi objective evolutionary algo- rithms:a comparative case study and the strength pareto ap- proach[J]. Evolutionary Computation, 1999,3(4) :257-271.
  • 9DING Da-Wei,YANG Guang-Hong.Static Output Feedback Control for Discrete-time Piecewise Linear Systems: an LMI Approach[J].自动化学报,2009,35(4):337-344. 被引量:7
  • 10徐慧英,赵建民,张泳,朱信忠.改进NSGA Ⅱ算法在车辆路径多目标优化问题中的应用[J].计算机工程与科学,2010,32(10):117-121. 被引量:13

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