DESIGNING A FRACTIONAL ORDER PID CONTROLLER FOR BIOREACTOR CONTROL
Hamed Banizaman · 2014
In the recent years, Evolutionary Algorithms (EAs) have been the topic of many researches through optimizations.Differential Evolution (DE) is one of the most popular optimization methods for real'valuedproblems and a large num ber of its variants have been proposed so far. However, bringingtogether different ideas that already led to successful DE versions is rare in the literature In this paper we propose a novel DE based MemeticAlgorithm(DEBMA) which hybridizes the differential evolution algorithm with a Local Search (LS)method to control the convergence rate of the population. In the proposed algorithm, some individuals are chosen for local refinement using a LS method, which leads to a smoother variation and a longer memory effect. The LS demonstrates a potential for interpreting evolution of the algorithm and to control its convergence. In this paper we describe an application of EAs to the design of fractional order proportional'integral'derivative ( FOPID) controllers which involve a fractional order integral and a fractional order derivative. Fractional order controllers are more complex to design due to five design parameters. Here we use EAs to design an optimal FOPID controller to control a Bioreactor plant.To show the performance of both the FOPID and the proposed algorithm, a comparison between the designed controller using MA, simple DE and the conventional PID controller is presented.