Parameterized data-driven fuzzy model based optimal control of a semi-batch reactor |
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| Affiliation: | 1. Process Dynamics and Control Group, Chemical Engineering Division, CSIR-Indian Institute of Chemical Technology, Hyderabad 500007, India;2. Academy of Scientific and Innovative Research, CSIR-Indian Institute of Chemical Technology, Hyderabad 500007, India;1. College of Information Science and Technology, Donghua University, Shanghai, PR China;2. College of Information Engenering, Nanjing University of Finance and Economics, Nanjing, Jiangsu, PR China;3. School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing,Jiangsu, PR China;1. College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi 435002, PR China;2. College of Automation, Huazhong University of Science and Technology, Wuhan 430074, PR China;3. School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, PR China;4. School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, PR China;1. College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China;2. Zhejiang Provincial Key Laboratory of Communication networks and applications, Hangzhou 310023, China;1. College of Mechatronics and Control Engineering, Hubei Normal University, Huangshi 435002, China;2. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, China;3. School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China |
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| Abstract: | A parameterized data-driven fuzzy (PDDF) model structure is proposed for semi-batch processes, and its application for optimal control is illustrated. The orthonormally parameterized input trajectories, initial states and process parameters are the inputs to the model, which predicts the output trajectories in terms of Fourier coefficients. Fuzzy rules are formulated based on the signs of a linear data-driven model, while the defuzzification step incorporates a linear regression model to shift the domain from input to output domain. The fuzzy model is employed to formulate an optimal control problem for single rate as well as multi-rate systems. Simulation study on a multivariable semi-batch reactor system reveals that the proposed PDDF modeling approach is capable of capturing the nonlinear and time-varying behavior inherent in the semi-batch system fairly accurately, and the results of operating trajectory optimization using the proposed model are found to be comparable to the results obtained using the exact first principles model, and are also found to be comparable to or better than parameterized data-driven artificial neural network model based optimization results. |
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| Keywords: | Chemical engineering, Process control, Parameterized Data-driven fuzzy (PDDF) modeling Optimal control Orthonormal polynomial approximations Single rate and multirate cases |
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