Abstract
This work presents a hybrid controller based on the combination of fuzzy logic control (FLC) mechanism and internal model-based control (IMC). Neural network-based inverse and forward models are developed for IMC. After designing the FLC and IMC independently, they are combined in parallel to produce a single control signal. Mean averaging mechanism is used to combine the prediction of both controllers. Finally, performance of the proposed hybrid controller is studied for a nonlinear numerical plant model (NNPM). Simulation result shows the proposed hybrid controller outperforms both FLC and IMC.
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Hosen, M.A., Salaken, S.M., Khosravi, A., Nahavandi, S., Creighton, D. (2015). Hybrid Controller with the Combination of FLC and Neural Network-Based IMC for Nonlinear Processes. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_24
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DOI: https://doi.org/10.1007/978-3-319-26555-1_24
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