Using biogeography based optimization for tuning fuzzy pid controller

In this work, the design and simulation of Proportional Derivative Integral (PID) controller based on Biogeography Based Optimization (BBO) algorithm and Fuzzy PID has been presented for controlling the double tank systems. The PID controller has been designed using three methods that are Root locus design, Symmetrical optimum design and Magnitude optimum design method. Then the output response characteristics for each method have been simulated and tested. The results of these methods are compared graphically and numerically. Furthermore, optimizing the parameters of PID controller by using a new evolutionary algorithm BBO. In addition to a comparison between the characteristics of output responses of PID controller design methods and the characteristics of output response of BBO. In spite of the diversity in using PID controller, a lengthy time is needed for the trial and error tuning to find suitable PID parameters. Moreover, it is hard to achieve the desired control performance when applying PID controllers to some applications as in time varying systems because of the dynamic nature of these systems, so the most critical point in designing the PID controller is the selection of the parameters value of proportional, integral and derivative components. Because of the huge amount of values for these parameters, a lengthy time is needed to find the suitable values by trial and errors. So that, a systematic way must be used to get the optimum coefficients of PID terms. Therefore, control techniques are proposed to limit the drawback in the PID controller. One of these techniques is the Fuzzy logic controller which will be applied in this thesis. In addition to that the response enhancement by using Fuzzy Logic Controller is simulated. Furthermore graphically and numerically comparison with PID controller, BBO and Fuzzy logic controller is also introduced. In this study, we compared the results of using the BBO algorithm and the two Controllers PID and Fuzzified PID controller. First, we compared the results of the PID and the BBO algorithm in terms of overshoot, settling time, rise time, transient response and steady state error. Second, we compared the results of Fuzzified PID controller and BBO algorithm and PID controller. All simulations were presented using MATLAB Software and SIMULINK, which is used widely in control applications. Finally, the simulation results show that the output response of the system uses Fuzzified PID controller optimized by Biogeography based optimization is better than that of PID controller. Keywords: PID Controller, BBO Algorithm, Fuzzy PID Controller, Settling Time, Rise Time, Steady State Error, Response Chracteristics.