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|Title||Optimized Hybrid Fuzzy Fed PID Control of Nonlinear Systems|
The design of controllers for nonlinear systems in industry is a complex and difficult task. The development of nonlinear control techniques has been approached in many different ways with varied results. One approach which has shown promise for solving nonlinear control problems is the use of fuzzy logic control. This thesis proposes a new method utilizing proportional–integral-derivative (PID) control as a hybrid fuzzy PID controller for nonlinear system. The salient feature of the proposed approach is that it combines the fuzzy gain scheduling method and a fuzzy Fed PID controller to solve the nonlinear control problem. The resultant fuzzy rule base of the proposed controller contains one part for a non optimized controller. This single part of the rules uses the Takagi-Sugeno method for solving the nonlinear problem and compares it to the mamdani method. The number of fuzzy rules are minimized using a method of series reduction fuzzy rule base. The simulation results of a nonlinear system show that the performance of a Fed PID Hybrid Takagi-Sugeno fuzzy controller is better than that of the conventional fuzzy PID controller or Hybrid Mamdani fuzzy Fed PID controller, especially using the reduction of the number of fired rules.
|Publisher||the islamic university|
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