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Li-Wei Li,Mou-Quan Shen,Wen Qin 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.5
This paper investigates the simultaneous control and fault detection of Markovian jump systems with general transition rates allowed to be unknown and known with uncertainties. By introducing slack matrices, a new approach is developed to conquer the nonlinearity induced by unknown and uncertain transition rates. Then, sufficient conditions are presented to ensure the stochastic stability of the resultant closed-loop system and meet the robust and detection performance indices. Finally, an example is given to illustrate the effectiveness of the proposed theoretical results.
Jian Zhang,Wen-Bo Xie,Mou-Quan Shen,Ling Huang 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.5
The control problem of T-S fuzzy system with actuator amplitude, rate and acceleration saturations isaddressed in this paper, where state augmented feedback controller with LMIs (Liner Matrix Inequalities) constraintconditions are proposed. Dynamic decoupling method is applied to fuzzify the input magnitude saturation nonlinearityinto several sub-linear systems with fuzzy rules, thus a new T-S fuzzy system with input rate and accelerationsaturations can be obtained. Then PDC (parallel distributed compensation) and NPDC (non-PDC) controller areboth designed for the new T-S fuzzy system. The first and second order derivatives of input variable are given toobtain an augmented fuzzy system. As the augmented system output variable, the input rate is represented by firstorder derivative of the input term, the rate saturation constraint is described through norm bounded method. Moreover,the polytopic approach is used to replace the second order derivative of the input term, and a state augmentedfeedback NPDC controller is designed, the domain of attraction optimization process is also given. Finally, twopractical examples are presented to show the effectiveness of proposed method.