Fault Detection and Control of Process Systems

Vu Trieu Minh, Nitin Afzulpurkar and W. M. Wan Muhamad

Mathematical Problems in Engineering, 2007, vol. 2007, 1-20

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.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:080321

DOI: 10.1155/2007/80321

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