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Unknown input observer design for Takagi-Sugeno fuzzy stochastic system

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Abstract

This paper deals with the unknown input observer design for Takagi-Sugeno (T-S) fuzzy models subjected to measurement noise and stochastic noise. The method applies the singular system theory by considering the measurement noise as an augmented system state, and then an unknown input observer based on the techniques of singular systems is developed to estimate both the system states and measurement noise simultaneously. Under a necessary assumption, the error dynamic system of the observer is free from the unknown inputs. And the observer gain matrix is determined by means of minimum covariance matrix of state residual. Two simulation examples are given to illustrate the correctness and effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. College of Electronics and Information Engineering, Tongji University, Shanghai, China

    Shenghui Guo & Fanglai Zhu

  2. College of Electronics and Information Engineering, Suzhou University of Science and Technology, Suzhou, China

    Shenghui Guo

  3. College of Mechanical Engineering, Tongji University, Shanghai, 201804, China

    Liyun Xu

Authors
  1. Shenghui Guo
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  2. Fanglai Zhu
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  3. Liyun Xu
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Corresponding author

Correspondence to Liyun Xu.

Additional information

Recommended by Associate Editor Choon Ki Ahn under the direction of Editor Euntai Kim.

This work was supported by the National Nature Science Foundation of China (61074009). This work is also supported by the Research Fund for the Doctoral Program of Higher Education of China (20110072110015), Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology (PF110289), and Shanghai Leading Academic Discipline Project (B004).

Shenghui Guo received his M.S. degree from Hebei University of Technology, China, in 2009. He is currently pursuing a Ph.D. in Control Theory and Control Engineering in Tongji University, China. His research interests include observer design, model-based fault detection, and fault-tolerant control.

Fanglai Zhu received his Ph.D. degree in Control Theory and Control Engineering from Shanghai Jiao Tong University in 2001. Now he is a professor of Tongji University, China. His research interests include nonlinear observer design, chaotic synchronization based on observer, system identification, and model-based fault detection and isolation.

Liyun Xu received his Ph.D. degree from Shanghai Jiaotong University, China, in 2001, Postdoctor of Vienna University of Technology in 2005, and visiting scholar of Politecnico di Milano in 2010. He joined the faculty of Tongji University, and currently is an associate professor at the School of Mechanical Engineering. His research interests include system modelling and optimization, fault diagnosis, and intelligent manufacturing.

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Guo, S., Zhu, F. & Xu, L. Unknown input observer design for Takagi-Sugeno fuzzy stochastic system. Int. J. Control Autom. Syst. 13, 1003–1009 (2015). https://doi.org/10.1007/s12555-014-0190-5

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  • DOI: https://doi.org/10.1007/s12555-014-0190-5

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