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Dynamic R-parameter based integrated model predictive iterative learning control for batch processes
Affiliation:1. Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;2. Department of Chemical and Biomolecular Engineering, National University of Singapore, 117576, Singapore;1. Shanghai Key Laboratory of Power Station Automation Technology, Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;2. Department of Automation, College of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China;1. School of Automation & Electronics Engineering, Qingdao University of Science & Technology, Qingdao 266042, PR China;2. School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266042, PR China;3. Advanced Control Systems Lab, School of Electronics & Information Engineering, Beijing Jiaotong University, Beijing 100044, PR China;4. Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB T6G 2G6, Canada
Abstract:
Keywords:Batch process  Integrated learning control  Iterative learning control (ILC)  Model predictive control (MPC)  Model identification  Dynamic R-parameter
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