A hybrid control scheme of Sugeno Fuzzy PD-like System (SFPDS) and PID controller is introduced in this work. The idea of the proposed strategy is to manipulate the control error signal in two stages: the SFPDS first, and then the PID. The manipulated signal is finally provided as a control action to the system. The proposed control strategy aims at combining the benefits of utilizing the artificial intelligence in getting a better transient, and the PID in getting a better steady state error. In this work, the proposed Sugeno Fuzzy design is developed from modeling a self tuning Mamdani fuzzy system. The later is modeled using Adaptive Neuro Fuzzy Inference System (ANFIS) to reduce its number of rules, thus reducing its complexity. In case of PID, parameters selection was decided based on the value of Integral Square of Error (ISE). To prove the effectiveness of the proposed strategy, the proposed control scheme is applied to solve Twin Rotor MIMO System (TRMS) control problems. Simulation studies proved the effectiveness of proposed method. The results have proved the effectiveness of the proposed strategy in terms of achieving satisfactory control response in both planes of motion as compared with other peoples work.
Key words: Fuzzy PD-like System (SFPDS), Adaptive Neuro Fuzzy Inference System (ANFIS), Twin Rotor MIMO System (TRMS), Square of Error (ISE).
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