Create New Account
Login
Search or Buy Articles
Browse Journals
Browse Proceedings
Submit your Paper
Submission Information
Journal Review
Recommend to Your Library
Call for Papers
A NEW DESIGN METHOD OF OPTIMAL PID CONTROLLER WITH DYNAMIC PERFORMANCES CONSTRAINED
Xian H. Li, Hai B. Yu, and Ming Z. Yuan
References
[1] J.G. Ziegler and N.B. Nichols, Optimum settings for automaticcontrollers, Transactions of the ASME, 64, 1942, 759–768.
[2] J.G. Ziegler and N.B. Nichols, Process lags in automatic controlcircuits, Transactions of the ASME, 65, 1943, 433–444.
[3] G.H. Cohen and G.A. Coon, Theoretical consideration ofrelated control, Transactions of the ASME, 75, 1953, 827–834.
[4] C.R. Madhuranthakam, A. Elkamel, and H. Budman, Optimaltuning of PID controllers for FOPTD, SOPTD and SOPTDwith lead processes, Chemical Engineering and Processing, 47,2008, 251–264.
[5] D.H. Kim and J.H. Cho, Intelligent tuning of PID controllerwith disturbance function using immune algorithm, 2004 IEEEAnnual Meeting Fuzzy Information Processing, 1 (27–30), 2004,286–291.
[6] Z.L. Gaing, A particle swarm optimization approach for opti-mum design of PID controller in AVR System, IEEE Trans-actions on Energy Conversion, 19 (2), 2004, 384–391.
[7] S. Pothiya and I. Ngamroo, Optimal fuzzy logic-based PIDcontroller for load–frequency control including superconduct-ing magnetic energy storage units, Energy Conversion andManagement, 49, 2008, 2833–2838.
[8] M. Zhuang and D.P. Atherton, Automatic tuning of opti-mum PID controllers, IEE Proceedings D Control Theory andApplications, 140 (3), 1993, 216–224.
[9] S. Daley and G.P. Liu, Optimal PID tuning using direct searchalgorithms, Computing Control Engineering Journal, 10 (2),1999, 51–56.
[10] H. Panagopoulos, K.J. Astrom, and T. Hagglund, Designof PID controllers based on constrained optimization, IEEProceedings, Control Theory and Applications, 149 (1), 2002,32–40.
[11] C. Hwang and C.Y. Hsiao, Solution of a non-convex optimiza-tion arising in PI/PID control design, Automatica, 38, (2002),1895–1904.
[12] C.H. Hsieh and J.H. Chou, Design of optimal PID controllers forPWM feedback systems with bilinear plants, IEEE Transactionon Control Systems Technology, 15 (6), 2007, 1075–1079.
[13] J.B. He, Q.G. Wang, and T.H. Lee, PI/PID controller tuningvia LQR approach, Proc. 37th IEEE Conference on Decisionand Control, Tampa, F., 1998, 1177–1182.260
[14] G.R. Yu and R.C. Hwang, Optimal PID speed control of brush-less DC motors using LQR approach, 2004 IEEE InternationalConference on Systems, Man and Cybernetics, The Hague,Netherlands 473–478.
[15] P.B. Dickinson and A.T. Shenton, A parameter space approachto constrained variance PID controller design, Automatica, 45,2009, 830–835.
[16] J.C. Basilio and S.R. Matos, Design of PI and PID controllerswith transient performance specification, IEEE Transactionson Education, 45 (4), 2002.
[17] M. Saeki, Fixed structure PID controller design for standardH∞ control problem, Automatica, 42, 2006, 93–100.
[18] O. Lequin, M. Gevers, M. Mossberg, E. Bosmans, and L. Triest,Iterative feedback tuning of PID parameters: Comparison withclassical tuning rules, Control Engineering Practice, 11, 2003,1023–1033.
[19] M. Xu, S.Y. Li, C.K. Qi, and W.J. Cai, Auto-tuning ofPID controller parameters with supervised receding horizonoptimization, ISA Transactions, 44, 2005, 491–500.
[20] G.L. Luo and G.N. Saridis, LQ design of PID controllers forrobot arms, IEEE Journal of Robotics and Automation, 1 (3),1985, 152–159.
[21] X.H. Li, H.B. Yu, and M. Z. Yuan, Design of an optimalPID controller based on Lyapunov approach, Proceedings of2009 International Conference on Information Engineeringand Computer Science (ICIECS-2009), Wuhan, 19–20, 2009.
[22] X.H. Li, H.B. Yu, M.Z. Yuan, and J. Wang, Design of robustoptimal proportional–integral–derivative controller based onnew interval polynomial stability criterion and Lyapunov the-orem in the multiple parameters’ perturbations circumstance,IET Control Theory and Applications, 4 (11), 2010, 2427–2440.
[23] D.E. Rivera, M. Morari, and S. Skogestad, Internal modelcontrol 4 PID controller design, Industrial and EngineeringChemistry, Process Design and Development, 25, 1986, 252–265.
[24] S. Skogestad, Simple analytic rules for model reduction andPID controller tuning, Journal of Process Control, 13 (4), 2003,291–309.
[25] M. Veronesi and A. Visioli, Performance assessment and re-tuning of PID controllers for integral processes, Journal ofProcess Control, 20, 2010, 261–269.
[26] A. Visioli, A new design for a PID plus feedforward controller,Journal of Process Control, 14, 2004, 457–463.
[27] K.K. Tan, T.H. Lee, and X. Jiang, On-line relay identification,assessment and tuning of PID controller, Journal of ProcessControl, 11, 2001, 483–496.
[28] Q.G. Wanga, Z.P. Zhang, K.J. Astrom, and L.S. Chek, Guar-anteed dominant pole placement with PID controllers, Journalof Process Control, 19, 2009, 349–352.
[29] K.J. ˚Astr¨om and T. H¨agglund, Automatic tuning of simpleregulators with specifications on phase and amplitude margins,Automatica, 20 (5), 1984, 645–651.
[30] K.J. ˚Astr¨om and T. H¨agglund, PID controllers: Theory, designand tuning, 2nd ed. (Research Triangle Park, NC: InstrumentSociety of America, 1995).
[31] K.J. Astrom and T. Hagglund, The future of PID control,Control Engineering Practice, 9, 2001, 1163–1175.
[32] V. Bob´al, J. B¨ohm, J. Fessl, and J. Mach´acek, Digital self-tuning controllers: Algorithms, implementation and applica-tions (Advanced Textbooks in Control and Signal Processing),1st ed. (Berlin Heidelberg: Springer, 2005), 53–136. ISBN-10:1852339802
[33] A. Leva, PID autotuning algorithm based on relay feedback,IEE Proc. D, Control Theory and Applications, 140 (5), 1993,328–338.
[34] A.Visioli, Optimal tuning of PID controllers for integral andunstable processes, IEE Proceedings on Control Theory Appli-cation, 148 (2), 2001, 180–184.
[35] X.H. Li, H.B. Yu, M.Z. Yuan, C.Z. Zang, and Z. Wang, OptimalMIMO PID controllers for the MIMO processes, Proc. ASME2011 Dynamic Systems and Control Conference, Arlington,VA, 2011, 1–8.
[36] J. Lan, J. Cho, D. Erdogmus, J.C. Principe, M.A. Motter,and J. Xu, Local linear PID controllers for nonlinear control,Control and Intelligent Systems, 1, 2005, 26–34.
[37] T.R. Rangaswamy, J. Shanmugam, and K.P. Mohammed,Adaptive fuzzy tuned PID controller for combustion of utilityboiler, Control and Intelligent Systems, 1, 2005, 63–71.
[38] M. Tokuda, T. Yamamoto, and Y. Monden, A neural-net basedPID controllers for nonlinear multivariable systems, Controland Intelligent Systems, 1, 2005, 36–46.
[39] J.J. D’Azzo and C.H. Houpis, ‘Linear control system analysisand design’, 2nd ed. (New York, USA: McGraw-Hill, Inc.,1981), 483–522.
[40] M.D. Tong, Linear system theory and design, 2nd ed. (Heifei,China: University of Science and Technology of China press,2004), (in Chinese), 208–245.
[41] G. Obinata and B.D. Anderson, Model reduction for controlsystem design, (Berlin Heidelberg: Springer, 2001), 22–42.
[42] B.C. Moore, Principal component analysis in linear systems:Controllability, observability, and model reduction, IEEETransactions on Automatic Control, 26 (1), 17–32.
[43] D.G. Meyer and S. Srinivasan, Balancing and model reductionfor second-order form linear systems, IEEE Transactions onAutomatic Control, 41 (11), 1632–1644.
[44] M.J. Bosley and F.P. Less, Methods for the reduction of highorder state variable models to simple transfer function models,Automatica, 8 (6), 1972, 765–775.
[45] C.M. Liaw, C.T. Pan, and Y.C. Chen, Reduction of transferfunctions using dispersion analysis and the continued fractionmethod, International Journal of Systems Science, 17 (5),1986, 807–817.
[46] W. Qi and W. Shifu, Principle of automatic control, 2nd ed.(Tsinghua University Press 2006) (in Chinese), 152–402.
[47] D.E. Seborg, T.F. Edgar, and D.A. Mellichamp, Process dy-namic and control, in J.C. Wang and Y.H. Jin (Trans.),2nd ed. (Publishing House of Electronic Industry, 2006), (inChinese), 96–360.
[48] S.S. Hu, Automatic control theory, 4th edition, Sciences press,Beijing, 2001, (in Chinese), 77–269.
[49] T.F. Coleman and Y. Li, On the convergence of reﬂectiveNewton methods for large-scale nonlinear minimization subjectto bounds, Mathematical Programming, 67(2), 1994, 189–224.
[50] T.F. Coleman and Y. Li, A reﬂective Newton method forminimizing a quadratic function subject to bounds on someof the variables, SIAM Journal on Optimization, 6(4), 1996,1040–1058.
[51] D.F. Shanno, Conditioning of quasi-Newton methods for func-tion minimization, Mathematics of Computing, 24, 1970, 647–656.
[52] R.K. Brayton, S.W. Director, G.D. Hachtel, and L. Vidigal,A new algorithm for statistical circuit design based on quasi-Newton methods and function splitting, IEEE Transactionson Circuits and Systems, 26(9), September 1979, 784–794.
[53] R. Fletcher and M.J.D. Powell, A rapidly convergent descentmethod for minimization, Computer Journal, 6, 1963, 163–168.
[54] M.A. Branch, T.F. Coleman, and Y. Li, A subspace, inte-rior, and conjugate gradient method for large-scale boundcon-strained minimization problems, SIAM Journal on ScientificComputing, 21(1), 1999, 1–23.
[55] T.F. Coleman and A. Verma, A preconditioned conjugategradient approach to linear equality constrained minimization,Computational Optimization and applications, 20(1), 61–72.
[56] T. Steihaug, The conjugate gradient method and trust re-gions in large scale optimization, SIAM Journal on NumericalAnalysis, 20, 1983, 626–637.
[57] R.J. Vanderbei and D.F.Shanno, An interior point algorithmfor non-convex nonlinear programming, Computational Opti-mization and Applications, 13, 1999, 231–252.
[58] D.F. Shanno and R.J. Vanderbei, Interior point methods fornon-convex nonlinear programming: Orderings and higher-order methods, Mathematical Programming, 87, 2000, 303–316.
[59] Y. Zhang, Solving large-scale linear programs by interiorpointmethods under the MATLAB environment, Technical ReportTR 96-01, Department of Mathematics and Statistics, Univer-sity of Maryland, Baltimore County, Baltimore, MD, 1995.261,
Important Links:
Abstract
DOI:
10.2316/Journal.201.2012.4.201-2392
From Journal
(201) Mechatronic Systems and Control (formerly Control and Intelligent Systems) - 2012
Go Back