Abstract
In this paper, PID controller with ant colony optimization is developed for the conical tank. Ant Colony Optimization (ACO) is a recently developed meta-heuristic approach for solving hard combinational optimization problems. Each individual ant can find a solution or at least part of a solution to the optimization problem on its own, but only when many ants work together they can find the optimal solution. Since the optimal solution can only be found through the global cooperation of all the ants in a colony, it is an emergent result of such cooperation. The results of PID controller with ant colony optimization provides a remarkable improvement in tracking a given set point, when compared with the Ziegler Nichols closed loop tuning and feed forward plus feedback controller tuning methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
