Performance analysis of model-free PID tuning of MIMO systems based on simultaneous perturbation stochastic approximation

Expert Systems with Applications

Volumn 41, Issue 14, 2014, Pages 6361-6370

  Ahmad, Mohd Ashraf ^a   Azuma, Shun Ichi ^a   Sugie, Toshiharu ^a  

^a KYOTO UNIVERSITY   (Japan)

Author keywords

MIMO systems; Model free design; PID controller; Stochastic optimization

Indexed keywords

MIMO SYSTEMS;

EXTENSIVE SIMULATIONS; MODEL FREE; PERFORMANCE ANALYSIS; PERFORMANCE COMPARISON; PID CONTROLLERS; SIMULTANEOUS PERTURBATION STOCHASTIC APPROXIMATION; STOCHASTIC OPTIMIZATIONS; TRACKING PERFORMANCE;

OPTIMIZATION;

EID: 84901417517     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2014.03.055     Document Type: Article

References (29)

1. B.B. Alagoz, A. Ates, and C. Yeroglu Auto-tuning of pid controller according to fractional-order reference model approximation for dc rotor control Mechatronics 23 7 2013 789 797
2. I. Baba, S. Azuma, and T. Sugie Controller design for optimizing fuel consumption of hybrid electric vehicles: A model-free approach based on simultaneous perturbation stochastic approximation Transactions of the Society of Instrument and Control Engineers 49 9 2013 887 894
3. W.-D. Chang A multi-crossover genetic approach to multivariable pid controllers tuning Expert Systems with Applications 33 3 2007 620 626 (Pubitemid 46366667)
4. W.-D. Chang Pid control for chaotic synchronization using particle swarm optimization Chaos, Solitons Fractals 39 2 2009 910 917
5. L.d.S. Coelho, and V.C. Mariani Firefly algorithm approach based on chaotic tinkerbell map applied to multivariable pid controller tuning Computer and Mathematics with Applications 64 8 2012 2371 2382
6. E. Davison Control of a distillation column with pressure variation Transaction of the Institute of Chemical Engineers 45 1967 229 250
7. H.-b. Duan, D.-b. Wang, and X.-f. Yu Novel approach to nonlinear pid parameter optimization using ant colony optimization algorithm Journal of Bionic Engineering 3 2 2006 73 78
8. Z.-L. Gaing A particle swarm optimization approach for optimum design of pid controller in avr system IEEE Transactions on Energy Conversion 19 2 2004 384 391
9. H 2 optimization toolbox in slicot. Technical report, European community BRITE-EURAM III thematic networks programme NICONET, SLICOT working note 1999-12.
10. Hsiao, Y.-T.;Chuang, C.-L.; Chien, C.-C. (2004). Ant colony optimization for designing of pid controllers. In IEEE international symposium on computer aided control systems design (pp. 321-326). (Pubitemid 40788535)
11. M.W. Iruthayarajan, and S. Baskar Evolutionary algorithms based design of multivariable pid controller Expert systems with Applications 36 5 2009 9159 9167
12. Jaafar, H. I.;Mohamed, Z.;Abidin, A. F. Z.; Ghani, Z. A. (2012). Pso-tuned pid controller for a nonlinear gantry crane system. In IEEE international conference on control system, computing and engineering (ICCSCE) (pp. 515-519).
13. D.H. Kim, A. Abraham, and J.H. Cho A hybrid genetic algorithm and bacterial foraging approach for global optimization Information Sciences 177 18 2007 3918 3937 (Pubitemid 46961984)
14. S. Kirkpatrick, C.D. Gelatt, and M.P. Vecchi Optimization by simulated annealing Science 220 4598 1983 671 680
15. Korani, W. M.;Dorrah, H. T.; Emara, H. M. (2009). Bacterial foraging oriented by particle swarm optimization strategy for pid tuning. In IEEE international symposium on computational intelligence in robotics and automation (CIRA) (pp. 445-450).
16. M.I. Menhas, M. Fei, L. Wang, and L. Qian Real/binary co-operative and co-evolving swarms based multivariable pid controller design of ball mill pulverizing system Energy Conversion and Management 54 1 2012 67 80
17. M.I. Menhas, L. Wang, M. Fei, and H. Pan Comparative performance analysis of various binary coded pso algorithms in multivariable pid controller design Expert Systems with Applications 39 4 2012 4390 4401
18. Nasir, A. N. K.;Tokhi, M.;Ghani, N.; Ahmad, M. A. (2012). A novel hybrid spiral dynamics bacterial chemotaxis algorithm for global optimization with application to controller design. In UKACC international conference on control (CONTROL) (pp. 753-758).
19. F.J. Solis, and R.J.-B. Wets Minimization by random search techniques Mathematics of Operations Research 6 1981 19 30
20. J.C. Spall Multivariate stochastic approximation using a simultaneous perturbation gradient approximation IEEE Transactions on Automatic Control 37 3 1992 332 341
21. J.C. Spall A one-measurement form of simultaneous perturbation stochastic approximation Automatica 33 1997 109 112 (Pubitemid 127416331)
22. J.C. Spall Adaptive stochastic approximation by the simultaneous perturbation method IEEE Transactions on Automatic Control 45 2000 1839 1853 (Pubitemid 32067073)
23. Steinbuch, M. (1989). Dynamic modelling and robust control of a wind energy conversion system (Ph.D. thesis). Delft University of Technology.
24. P. Xu, G. Li, and K. Wang Self tuning of pid controller based on simultaneous perturbation stochastic approximation Lecture Notes in Electrical Engineering 139 2012 647 652
25. Z. Yachen, and H. Yueming On pid controllers based on simulated annealing algorithm 27th Chinese control conference, CCC 2008 2008 IEEE 225 228
26. G. Yin Rates of convergence for a class of global stochastic optimization algorithms SIAM Journal on Optimization 10 1 1999 99 120
27. Yuan, Q. (2008). A model free automatic tuning method for a restricted structured controller by using simultaneous perturbation stochastic approximation (spsa). In American control conference (pp. 1539-1545).
28. 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 17 12 2009 1380 1387
29. J. Zhang, J. Zhuang, H. Du, and S. Wang Self-organizing genetic algorithm based tuning of pid controllers Information Sciences 179 7 2009 1007 1018