Comparison of ABC and Ant Colony Algorithm Based Fuzzy Controller for an Inverted Pendulum
Anita Khosla1, Leena G. M2, K. Soni3
1Anita Khosla, Research Scholar, Department of EEE, Engineering and Technology, Manav Rachna International University, Faridabad (Haryana), India.
2Dr. Leena G, Professor, Department of EEE, Engineering and Technology, Manav Rachna International University, Faridabad (Haryana), India.
3M. K. Soni, Exe. Director and Dean, Department of Electronic & Control System, Engineering and Technology, Manav Rachna International University, Faridabad (Haryana), India.
Manuscript received on 8 August 2013 | Revised Manuscript received on 18 August 2013 | Manuscript Published on 30 August 2013 | PP: 133-139 | Volume-3 Issue-3, August 2013 | Retrieval Number: C1144083313/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Fuzzy logic is a practical, robust, economical and intelligent alternative for controller design of complex systems. Choosing appropriate fuzzy rules is essential for a fuzzy logic controller to perform at the desired level. Various evolutionary algorithms are used to find an optimal set of fuzzy rules in the literature. In this paper, an artificial bee’s colony (ABC) optimization algorithm and Ant colony algorithm are used to optimize the fuzzy membership functions to control the deviation in pendulum angle and velocity. The proposed control techniques are implemented in MATLAB/Simulink platform and the control performances are evaluated. With the ABC based fuzzy, the inverted pendulum is remaining in the steady position with less error.
Keywords: Inverted Pendulum, Angle, Velocity, Integrated Control, ABC Algorithm, Fuzzy Controller, Ant Colony Algorithm.
Scope of the Article: Fuzzy Logics