期刊文献+

Lipschitz非线性系统未知输入观测器设计 被引量:5

Design of Observer with Unknown Input for Lipschitz Nonlinear Systems
下载PDF
导出
摘要 针对观测器匹配条件不满足情况下的Lipschitz非线性系统状态估计和未知输入重构问题,提出了一种未知输入观测器设计方法。首先,通过构造辅助输出向量,突破了观测器匹配条件的限制,并设计高阶、高增益滑模微分器实现对辅助输出向量及其微分的精确估计;之后,在辅助输出及其微分精确估计的基础上,设计具有滑模控制律和自适应调节律的自适应鲁棒滑模观测器,并提出了一种未知输入重构方法。该观测器设计方法不需知道Lipschitz常数,其大小可通过自适应调节律调节,且信息重构具有避免直接使用系统输出微分的优点。仿真结果表明,所设计的未知输入观测器不仅在观测器匹配条件不满足情况下可以实现对状态的渐进估计以及对未知输入重构之目的,而且自适应调节律能够在约5s时间内实现对Lipschitz常数的自适应调节。 A scheme to design observer with unknown input and unknown input reconstruction for Lipschitz nonlinear systems is proposed when the observer matching condition is not satisfied. An auxiliary output vector is constructed to satisfy the observer matching condition, and a highorder sliding mode differentiator with highgain is designed to exactly estimate the auxiliary output vector and its derivative. Then, an adaptive robust sliding mode observer which complies with a robust sliding mode control law and an adaptation law is developed based on the estimations of the auxiliary output vector and its derivative, and an unknown input reconstruction method is derived without using the derivative information of system’s output vector. The Lipschitz constant does not need to be known and is adjusted using the adaptive law. The method of unknown input reconstruction avoids the direct use of the derivative information of system’s output. Simulation results show that states and unknown inputs can be gradually estimated by the proposed unknown input observer when the observer matching condition is not satisfied, and that the Lipschitz constant can be adjusted within 5 seconds by the proposed adaptation law.
出处 《西安交通大学学报》 EI CAS CSCD 北大核心 2013年第8期87-92,共6页 Journal of Xi'an Jiaotong University
基金 国家自然科学基金资助项目(61074009) 教育部高等学校博士学科点专项科研基金资助项目(20110072110013) 上海市重点学科资助项目(B004) 河南省教育厅科学技术研究重点资助项目(13B413035 13B413028)
关键词 未知输入观测器 未知输入重构 滑模观测器 unknown input observer unknown input reconstruction sliding mode observer
  • 相关文献

参考文献15

  • 1WANG S H, DAVISON E J, DORATO P. Observing the states of systems unmeasurable disturbances[J]. IEEE Transactions on Automatic Control, 1975, 20 (5): 716717.
  • 2PANUSKA V. A new form of the extended Kalman filter for parameter estimation in linear systems with correlated noise[J]. IEEE Transactions on Automatic Control, 1980,25 (2) : 229235.
  • 3BENALLOUCH M, BOUTAYEB M, OUTBIB R, et al. Nonlinear estimation of states and unknown inputs for communication systems[CJ II Proceedings of IEEE International Conference on Signal Processing and Communications. Piscataway, NJ , USA: IEEE, 2007: 696699.
  • 4BARSHALOM Y. Optimal simultaneous state esti?mation and parameter identification in linear discrete?time system[J]. IEEE Transactions on Automatic Control, 1972,17(3) :308319.
  • 5Y AN Xinggang, EDWARDS C. Adaptive sliding-mode observer-based fault reconstruction for nonlinear sys?tems with parametric uncertainties[J]' IEEE Trans actions on Industrial Electronics, 2008,35 (11) : 4029 4036.
  • 6RAO S, BUSS M, UTKIN V. Simultaneous state and parameter estimation in induction motors using first?and-second-order sliding modes[J]. IEEE Transac?tions on Industrial Electronics, 2009, 56 (9) : 3369 3376.
  • 7DING Zhengtao. Differential stability and design of re?duced-order observers for non-linear systems[J]. lET Control Theory &. Applications, 2011.5(2) :315322.
  • 8LI j ianmin , ZHENG Yunfeng, SHEN Zhipeng. Non?linear observer design for a class of nonlinear systems with non-Lipschitz nonlinearities of the unmeasured states[CJ II Proceeding of the 29th Chinese Control Conference. Beijing, China: Chinese Association of Automation, 2010: 3531 3533.
  • 9SHEN Zhongyu, ZHAO j in , XU[ie , et al. Nonlinear unknown input observer design by LMI for Lipschitz nonlinear systems[CJ II Proceeding of the 8th World Congress on Intelligent Control and Automation. Bei?jing, China: Chinese Association for Artificial Intelli?gence, 2010:34503453.
  • 10KALSI K, LIAN J M,HUI S, et al. Sliding-mode ob?servers for systems with unknown inputs: a highgain approach[J]. Automatica , 2010.46(2) :347353.

二级参考文献13

  • 1Reif K, Sonnemann F, Unbehauen R. Nonlinear state observation usingH-∞-filtering Riccati design. IEEE Transactions on Automatic Control, 1999, 44(1): 205-208
  • 2Oisiovici R M, Cruz S L. State estimation of batch distillation columns using an extended Kalman filter. Chemical Engineering Science, 2000, 55: 4667-4680
  • 3Portu G, Aragoness C, Baratti R, Servida A. Monitoring of a CO oxidation reactor through a grey rnodel-based EKF observer. Chemical Engineering Science, 2000,55: 331-338
  • 4Hou M, Pugh A C. Observer with linear error dynamics for nonlinear multi-output systems. Systems & Control Letters, 1999, 37:1-9
  • 5Xia X, Gao W. Nonlinear observer design by observer error linearization. SIAM Journal of Control and Optimization, 1989, 27(1) :199-216
  • 6Bestle D, Zeitz M. Canonical form observer design for nonlinear time variable systems. International Journal Control, 1983, 38(2): 419-431
  • 7Krener A J, Xiao M. Observers for linearly unobservable nonlinear systems. Systems & Control Letters, 2002, 46:281 -288
  • 8Rajamani R. Observer for lipschitz nonlinear systems. IEEE Transactions on Automatic Control, 1998, 43(3): 397-401
  • 9Besancon G. Remarks on nonlinear adaptive observer design. Systems & Control Letters, 2000, 41:271-280
  • 10Germani A, Manes C, Pepe P. A new approach to state observation of nonlinear systems with delayed output.IEEE Transactions on Automatic Control, 2002, 47(1): 96- 101

共引文献9

同被引文献33

  • 1CHEN J, PATTON R J. Robust model-based fault di- agnosis for dynamic systems [M]. New York, USA: Springer Publishing Company, 2012.
  • 2EDWARDS C, SPURGEON S K, PATTON R J. Sliding mode observers for fault detection and isolation [J]. Automatica, 2000, 36(4): 541-553.
  • 3YAN X G, EDWARDS C. Adaptive sliding-mode- observer-based fault reconstruction for nonlinear sys- tems with parametric uncertainties [J]. IEEE Trans- actions on Industrial Electronics, 2008, 55(11): 4029- 4036.
  • 4HAOUARI F A, DJEMAI M, CHERKI 13. Sliding mode observers for T-S fuzzy systems with applicationto sensor fault estimation [C] // Proceedings of the 3rd International Conference on Control, Engineering Information Technology. Piscataway, NJ, USA: IEEE, 2015: 1-5.
  • 5LIU M, CAO X, SHI P. Fault estimation and tolerant control for fuzzy stochastic systems [J]. IEEE Trans- actions on Fuzzy Systems, 2013, 21(2): 221-229.
  • 6LCHALA D, MARX B, RAGOT J, et al. Sensor fault tolerant control of nonlinear Takagi-Sugeno sys- tems: application to vehicle lateral dynamics [J]. In- ternational Journal of Robust and Nonlinear Control, 2015, 26(7): 1376-1394.
  • 7HUANG Shengjuan, YANG Guang hong. Fault toler- ant controller design for T-S fuzzy systems with time- varying delay and actuator faults: a k-step fault- estimation approach [J]. IEEE Transactions on Fuzzy Systems, 2014, 22(6): 1526-1540.
  • 8YANG Qinmin, SAM GE Shuzhi, SUN Youxian. Adaptive actuator fault tolerant control for uncertain nonlinear systems with multiple actuators [J]. Auto- matica, 2015, 60: 92-99.
  • 9JIANG Bin, WANG Jianliang, SOH Y C. An adaptive technique for robust diagnosis of faults with independ- ent effects on system outputs [J]. International Jour- nal of Control, 2002, 75(11): 792-802.
  • 10JIANG B, STAROSWIECKI M, COCQUEMPOT V. Fault accommodation for nonlinear dynamic systems [J]. IEEE Transactions on Automatic Control, 2008, 51(9) :1578-1583.

引证文献5

二级引证文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部