CONTROL OF DEAD-TIME SYSTEMS USING HYBRID ANT COLONY OPTIMIZATION

摘要

This paper introduces two improved forms of the ant colony optimization (ACO) algorithm applied to a proportional integral derivative (PID) controller and Smith predictor design. Derivative free optimization methods, namely simplex derivative based pattern search (SDPS) and implicit filtering (IMF), are used to intensify the search mechanism in the ACO algorithm with improved convergence over the original ACO. The effectiveness of the controller schemes using the proposed algorithms, namely SDPS-ACO, and IMF-ACO, is demonstrated using unit step set point response for a class of dead-time systems, and the results are compared with some existing methods of controller tuning.