Optimization design of pid controller parameters based on improved E.Coli foraging optimization algorithm

E.Coli foraging optimization algorithm is an evolutional algorithm and imitates the behavior of E.Coli bacteria. In this paper, a novel improved E.Coli foraging optimization algorithm (IEFOA) for parameter tuning of PID controller has been proposed. IEFOA is presented with three main operators, which include a tumbling operator, a swimming operator and a tracing operator that at the same time records the optimal position of individual E.Coli in order to update the locations of swarm. Instead of using traditional analysis algorithm, the parameters of PID controller such as proportional gain, integral factor, differential coefficient are selected and optimized by IEFOA. The effectiveness of the proposed optimization algorithm is tested by simulation experiments of the common one-order and two-order industrial models. The simulation shows excellent results in term of response time and output overshoot for a step reference. The IEFOA approach provides an attractive method for the design of PID controller parameters.