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• W1985944288 abstract "This paper develops a stochastic hybrid model-based control system that can determine online the optimal control actions, detect faults quickly in the control process, and reconfigure the controller accordingly using interacting multiple-model (IMM) estimator and generalized predictive control (GPC) algorithm. A fault detection and control system consists of two main parts: the first is the fault detector and the second is the controller reconfiguration. This work deals with three main challenging issues: design of fault model set, estimation of stochastic hybrid multiple models, and stochastic model predictive control of hybrid multiple models. For the first issue, we propose a simple scheme for designing faults for discrete and continuous random variables. For the second issue, we consider and select a fast and reliable fault detection system applied to the stochastic hybrid system. Finally, we develop a stochastic GPC algorithm for hybrid multiple-models controller reconfiguration with soft switching signals based on weighted probabilities. Simulations for the proposed system are illustrated and analyzed." @default.
• W1985944288 created "2016-06-24" @default.
• W1985944288 creator A5009603257 @default.
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• W1985944288 date "2007-01-01" @default.
• W1985944288 modified "2023-09-25" @default.
• W1985944288 title "Fault Detection and Control of Process Systems" @default.
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• W1985944288 doi "https://doi.org/10.1155/2007/80321" @default.
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