Fault detection for discrete-time fuzzy systems with measurement errors using interval observers |
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| Institution: | 1. School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110870, PR China;2. College of Information Science and Engineering, Northeastern University, Shenyang 110819, PR China;1. University of Tunis El Manar, National Engineering School of Tunis, LR11ES20 Analysis, Conception and Control of Systems Laboratory, Tunis 1002, Tunisia;2. University of Monastir, National Engineering School of Monastir, Monastir 5035, Tunisia;3. School of Astronautics, Harbin Institute of Technology, Harbin 150001, PR China;4. Conservatoire National des Arts et Métiers (CNAM), CEDRIC-Lab, Paris 75003, France;1. School of Science, Tianjin University of Technology and Education, Tianjin 300222, China;2. College of Artificial Intelligence, Nankai University, Tianjin 300350, China |
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| Abstract: | This paper presents an interval observer-based fault detection (FD) strategy for discrete-time T–S fuzzy systems with measurement errors. The system and measurement outputs are selected as the premise variables of plant and observer respectively. The bounds of mismatch items caused by the measurement errors are established by covering matched region, mismatched left adjacent region and right adjacent region. Piecewise Lyapunov function, taking full account of possible transitions, is employed to drive observer design condition. FD is turned into optimization problem with disturbance attenuation, fault sensitivity and nonnegativity constraints. The decision is implemented by judging whether zero is excluded from the residual interval. Finally, simulation is explored to verify the scheme. |
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