Improved state space model predictive fault-tolerant control for injection molding batch processes with partial actuator faults using GA optimization |
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| Affiliation: | 1. The Belt and Road Information Research Institute, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;2. Key Laboratory of Advanced Control and Optimization for Chemical Processes, Shanghai 200237, China;3. Department of Information Service & Intelligent Control, Shenyang Institute of Automation, Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China |
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| Abstract: | A novel model predictive fault-tolerant control (MPFTC) strategy adopting genetic algorithm (GA) is proposed for batch processes under the case of disturbances and partial actuator faults. Based on the extended state space model in which the tracking error is contained, there are more degrees of freedom provided for the controller design and better control performance is obtained. In order to enhance the control performance further, the GA is introduced to optimize the relevant weighting matrices in the cost function. The effectiveness of the proposed MPFTC approach is tested on the injection velocity regulation of the injection molding process. |
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| Keywords: | Model predictive fault-tolerant control Batch processes Genetic algorithm Partial actuator failure |
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