Adaptive observer and nonlinear control strategy for chemical reactors via neural networks |
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Authors: | ZEXIN HU XIWEN LU |
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Affiliation: | 1. Elite Business Machines Manufacturing Co. Ltd. , Elite Building 12, Nan Shan Road, Nan Shan District, Shenzhen, 518052, PR China;2. Department of Mathematics , East China University of Science and Technology , Shanghai, 200237, PR China |
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Abstract: | An adaptive observer and nonlinear feedback control strategy with constraints on control action are developed by using a supervised learning rule of a neural network and the theory of functional-link networks. The convergence of the adaptive observer and the stability of the control system are proven. They are applied to the control of an exothermic stirred-tank reactor. It is shown that an adaptive observer for concentration can be constructed for a reaction system when only temperature measurements are available on line. An adaptive observer is used to identify the pre-exponential Arrhenius constant and to provide on line estimation of the unmeasured reactant concentration for a nonlinear state-feedback controller. Simulations show that the combined observer/controller provides satisfactory closed-loop behaviour, fast responses and strong robustness. Estimated and actual concentration are in good agreement. A nonlinear feedback controller can provide effective feedback control over a wide range of operating conditions. |
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