Intelligent Modelling of MIMO Nonlinear Dynamic Process Plants for Predictive Control Purposes
نویسنده
چکیده
In this research, input/output data of a MIMO nonlinear system are used to create intelligent models. Multi layer perceprtrons and neuro-fuzzy networks are utilized for this purpose. For the purpose that these models suit predictive control in their best, a variety of subtle points should be considered. Recurrent models and subtractive clustering are used in this research, and a pre-processing is exerted on the columns of raw data. Then the prepared data are used to train models. A reliable checking process is also offered. A Catalytic Continuous Stirred Tank Reactor is used as case study. A computer model is used to gather input/data rather than a real one. Finally, the simulation is successfully performed to indicate the capabilities of intelligent modeling methods as well as the importance of the points offered through this paper.
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