Design of automated control system based on improved E.Coli foraging optimization algorithm

In industry process, though facing the difficulty of modeling, the historical accumulated object datum has not been made best use of. In this paper, a novel identification solution based on the improved E.Coli foraging algorithm (IEFOA) was 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. Furthermore, the systemic method for the design of automatic system integrated with the IEFOA was proposed. The total design procedure of control system includes two procedures. First, the model of the controlled object was estimated using the IEFOA based on the experiment data. Then the IEFOA was proposed to design the optimal parameters of controller. The simulation results show that the IEFOA plays an important role in the controlled object modeling and parameter optimal design of controller and IEFOA offers a new method for the whole control system design.