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ISRN Artificial Intelligence
Volume 2013 (2013), Article ID 543607, 11 pages
PSO-Based PID Controller Design for a Class of Stable and Unstable Systems
1Department of Instrumentation Engineering, Anna University, M.I.T Campus, Chennai 600 044, India
2Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai 600 119, India
Received 31 March 2013; Accepted 27 April 2013
Academic Editors: K. W. Chau and J. M. Molina López
Copyright © 2013 K. Latha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- A. O’Dwyer, Handbook of PI and PID Controller Tuning Rules, Imperial College Press, London, UK, 3rd edition, 2009.
- R. C. Panda, “Synthesis of PID controller for unstable and integrating processes,” Chemical Engineering Science, vol. 64, no. 12, pp. 2807–2816, 2009.
- M. A. Johnson and M. H. Moradi, PID Control: New Identification and Design Methods, chapter 2, Springer, London, UK, 2005.
- R. Padmasree and M. Chidambaram, Control of Unstable Systems, Narosa Publishing House, New Delhi, India, 2006.
- B. W. Bequette, Process Control—Modeling, Design and Simulation, Prentice Hall, New Delhi, India, 2003.
- U. S. Banu and G. Uma, “Fuzzy gain scheduled continuous stirred tank reactor with particle swarm optimization based PID control minimizing integral square error,” Instrumentation Science and Technology, vol. 36, no. 4, pp. 394–409, 2008.
- M. S. Arumugam and M. V. C. Rao, “On the performance of the particle swarm optimization algorithm with various inertia weight variants for computing optimal control of a class of hybrid systems,” Discrete Dynamics in Nature and Society, vol. 2006, Article ID 79295, 17 pages, 2006.
- M. S. Arumugam and M. V. C. Rao, “On the optimal control of single-stage hybrid manufacturing systems via novel and different variants of particle swarm optimization algorithm,” Discrete Dynamics in Nature and Society, vol. 2005, no. 3, pp. 257–279, 2005.
- R. M. Chen and C. M. Wang, “Project scheduling heuristics-based standard PSO for task-resource assignment in heterogeneous grid,” Abstract and Applied Analysis, vol. 2011, Article ID 589862, 20 pages, 2011.
- R. F. Abdel-Kader, “Particle swarm optimization for constrained instruction scheduling,” VLSI Design, vol. 2008, Article ID 930610, 7 pages, 2008.
- S. M. G. Kumar, R. Jain, N. Anantharaman, V. Dharmalingam, and K. M. M. S. Begam, “Genetic algorithm based PID controller tuning for a model bioreactor,” Indian Institute of Chemical Engineers, vol. 50, no. 3, pp. 214–226, 2008.
- M. Zamani, M. Karimi-Ghartemani, N. Sadati, and M. Parniani, “Design of a fractional order PID controller for an AVR using particle swarm optimization,” Control Engineering Practice, vol. 17, no. 12, pp. 1380–1387, 2009.
- I. Chiha, N. Liouane, and P. Borne, “Tuning PID controller using multiobjective ant colony optimization,” Applied Computational Intelligence and Soft Computing, vol. 2012, Article ID 536326, 7 pages, 2012.
- V. Rajinikanth and K. Latha, “Bacterial foraging optimization algorithm based pid controller tuning for time delayedunstable systems,” Mediterranean Journal of Measurement and Control, vol. 7, no. 1, pp. 197–203, 2011.
- V. Rajinikanth and K. Latha, “Identification and control of unstable biochemical reactor,” International Journal of Chemical Engineering Applications, vol. 1, no. 1, pp. 106–111, 2010.
- J. Kennedy and R. C. Eberhart, “Particle swarm optimization,” in Proceedings of the IEEE International Conference on Neural Networks, vol. 4, pp. 1942–1948, 1995.
- M. Araki and H. Taguchi, “Two-degree-of-freedom PID controllers,” International Journal of Control, Automation and Systems, vol. 1, no. 4, pp. 401–411, 2003.
- C. S. Jung, H. K. Song, and J. C. Hyun, “Direct synthesis tuning method of unstable first-order-plus-time-delay processes,” Journal of Process Control, vol. 9, no. 3, pp. 265–269, 1999.
- V. Vijayan and R. C. Panda, “Design of a simple setpoint filter for minimizing overshoot for low order processes,” ISA Transactions, vol. 51, no. 2, pp. 271–276, 2012.
- C. H. Lin, J. L. Chen, and Z. L. Gaing, “Combining biometric fractal pattern and particle swarm optimization-based classifier for fingerprint recognition,” Mathematical Problems in Engineering, vol. 2010, Article ID 328676, 14 pages, 2010.
- J. Zhang and K. W. Chau, “Multilayer ensemble pruning via novel multi-sub-swarm particle swarm optimization,” Journal of Universal Computer Science, vol. 15, no. 4, pp. 840–858, 2009.
- K. W. Chau, “Application of a PSO-based neural network in analysis of outcomes of construction claims,” Automation in Construction, vol. 16, no. 5, pp. 642–646, 2007.
- K. Chau, “Predicting construction litigation outcome using particle swarm optimization,” in Innovations in Applied Artificial Intelligence, vol. 3533 of Lecture Notes in Computer Science, pp. 571–578, Springer, New York, NY, USA, 2005.
- A. Alfi and H. Modares, “System identification and control using adaptive particle swarm optimization,” Applied Mathematical Modelling, vol. 35, no. 3, pp. 1210–1221, 2011.
- Y. Shi and R. Eberhart, “A modified particle swarm optimizer,” in Proceedings of the IEEE World Congress on Computational Intelligence, pp. 69–73, 1998.
- R. C. Eberhart and Y. Shi, “Tracking and optimizing dynamic systems with particle swarms,” in Proceedings of the Congress on Evolutionary Computation, vol. 1, pp. 94–100, Seoul, Republic of Korea, 2001.
- A. Nikabadi and M. Ebadzadeh, “Particle swarm optimization algorithms with adaptive inertia weight: a survey of the state of the art and a novel method,” IEEE Journal of Evolutionary Computation, 2008.
- G. Chen, X. Huang, J. Jia, and Z. Min, “Natural exponential inertia weight strategy in particle swarm optimization,” in Proceedings of the 6th World Congress on Intelligent Control and Automation (WCICA '06), pp. 3672–3675, Dalian, China, June 2006.
- R. F. Malik, T. A. Rahman, S. Z. M. Hashim, and R. Ngah, “New particle swarm optimizer with sigmoid increasing inertia weight,” International Journal of Computer Science and Security, vol. 1, no. 2, pp. 35–44, 2007.
- Y. Gao, X. An, and J. Liu, “A particle swarm optimization algorithm with logarithm decreasing inertia weight and chaos mutation,” in Proceedings of the International Conference on Computational Intelligence and Security (CIS ’08), vol. 1, pp. 61–65, 2008.
- G. P. Liu, J. B. Yang, and J. F. Whidborne, Multiobjective Optimization and Control, Printice Hall, New Delhi, India, 2008.
- J. G. Ziegler and N. B. Nichols, “Optimum settlings for automatic controllers,” Transactions of the ASME, vol. 64, pp. 759–768, 1942.
- V. Rajinikanth and K. Latha, “Optimization of PID controller parameters for unstable chemical systems using soft computing technique,” International Review of Chemical Engineering, vol. 3, no. 3, pp. 350–358, 2011.
- V. Rajinikanth and K. Latha, “Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm,” Applied Computational Intelligence and Soft Computing, vol. 2012, Article ID 214264, 12 pages, 2012.