Control of direct current motor using Ant Colony optimization

In this paper an Ant Colony optimization (ACO) algorithm is proposed as tuning mechanism for Proportional-Integral-Derivative(PID) controller of a direct current (DC) motor from a robotic arm. Firstly, the model of the DC motor, PID and ACO algorithm are described. Secondly, it is performed the PID tuning using Ziegler-Nichols (ZN), manual tuning and the ACO algorithm. Finally, the experimental results of PID and tuning methods are compared and discussed.

[1]  Stefano Stramigioli,et al.  PID motion control tuning rules in a damping injection framework , 2013, 2013 American Control Conference.

[2]  J. L. Febin Daya,et al.  A novel self - Tuning fuzzy based PID controller for speed control of induction motor drive , 2013, 2013 International Conference on Control Communication and Computing (ICCC).

[3]  Jinfeng Bai,et al.  Application of Fuzzy Logic Controller with Self-Tuning PID Parameters for Contral System of 40kg Coke Oven , 2013, 2013 Third International Conference on Instrumentation, Measurement, Computer, Communication and Control.

[4]  Rajeev Gupta,et al.  Application of Artificial Bee Colony Optimization for optimal PID tuning , 2014, 2014 International Conference on Advances in Engineering & Technology Research (ICAETR - 2014).

[5]  Yang Xu,et al.  Research on Direct Current Motor PID Control System Based on BP Neural Networks , 2010, 2010 2nd International Conference on Information Engineering and Computer Science.

[6]  A. TUSTIN,et al.  Automatic Control Systems , 1950, Nature.

[7]  P. N. Paraskevopoulos,et al.  Modern Control Engineering , 2001 .

[8]  Lin Yang,et al.  Adaptive PID regulator based on neural network for DC motor speed control , 2011, 2011 International Conference on Electrical and Control Engineering.

[9]  Hong Zhang,et al.  Parameter optimization of PID controllers based on genetic algorithm , 2010, 2010 International Conference on E-Health Networking Digital Ecosystems and Technologies (EDT).

[10]  A.E.A. Awouda,et al.  Refine PID tuning rule using ITAE criteria , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).

[11]  Rakosh Das Begamudre.  Electro-mechanical energy conversion with dynamics of machines , 1988 .

[12]  Hairi Zamzuri,et al.  PID controller optimization for a rotational inverted pendulum using genetic algorithm , 2011, 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization.

[13]  Oytun Eris,et al.  A direct digital PID tuning rule for SOPDT systems , 2012, 2012 2nd Australian Control Conference.

[14]  Yingyue Hu,et al.  Optimization of PID control for DC motor based on artificial bee colony algorithm , 2014, Proceedings of the 2014 International Conference on Advanced Mechatronic Systems.

[15]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[16]  Nikolaos I. Margaris,et al.  Explicit Analytical PID Tuning Rules for the Design of Type-III Control Loops , 2013, IEEE Transactions on Industrial Electronics.

[17]  K. G. Papadopoulos,et al.  Analytical tuning rules of digital PID controllers for integrating processes via the Symmetrical Optimum criterion , 2012, 2012 20th Mediterranean Conference on Control & Automation (MED).

[18]  O. Bendjeghaba,et al.  Firefly algorithm for optimal tuning of PID controller parameters , 2013, 4th International Conference on Power Engineering, Energy and Electrical Drives.

[19]  P. Pfeifer,et al.  Praise for Marketing Metrics Marketing Metrics 50+ Metrics Every Executive Should Master Library of Congress Cataloging-in-publication Data , 2006 .

[20]  Antonio Visioli,et al.  Optimal tuning rules for proportional-integral-derivative and fractional-order proportional-integral-derivative controllers for integral and unstable processes , 2012 .

[21]  Dwi Ana Ratna Wati.  Performance evaluation of swarm intelligence on model-based PID tuning , 2013, 2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM).

[22]  Dwi Ana Ratna Wati,et al.  Genetic algorithm-based PID parameters optimization for air heater temperature control , 2013, 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems.