Ant Colony Optimization based fixed order controller design and system simulations international conference on control, automation and systems (ICCAS 2011)

Thus far, researchers test several heuristic in order to produce the optimal solutions of the cost function and controller parameters. In this paper, an implementation of the Ant Colony Optimization (ACO) algorithm for the optimization of cost function and controller parameters has been discussed. To implement the ACO algorithm with a problem requires defining; cost function and the constraint. All simulation has been performed using a software program developed in the MATLAB environment. The simulation results show that ACO algorithm can be used to counterbalance the effect and improve the performance of any control system. Moreover, the proposed scheme overcomes the weaknesses of conventional fixed gain controller and improvement is accomplished in terms of settling time, oscillations and overshoot.