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Volumn 20, Issue 13, 2010, Pages 1483-1501

A comparative study on a novel model-based PID tuning and control mechanism for nonlinear systems

Author keywords

Adaptive control; Neural networks; Pid auto tuning; Support vector machines

Indexed keywords

ADAPTIVE CONTROL; AUTOTUNING; COMPARATIVE STUDIES; CONTROL ACTIONS; CONTROL APPROACH; CONTROL MECHANISM; CONTROL PERFORMANCE; CONVERGENCE PERFORMANCE; CONVERGENCE PROPERTIES; MEASUREMENT NOISE; MODEL-BASED; NARX MODELS; PARAMETER CONVERGENCE; PID CONTROLLERS; PID TUNING; PREDICTIVE MODELS; PROPORTIONAL INTEGRAL DERIVATIVES; SIMULATION RESULT; STEADY STATE TRACKING; SUPPORT VECTOR;

EID: 77956370697     PISSN: 10498923     EISSN: 10991239     Source Type: Journal    
DOI: 10.1002/rnc.1524     Document Type: Article
Times cited : (46)

References (29)
  • 4
    • 85008048184 scopus 로고    scopus 로고
    • Auto-tuned PID controller using a modelpredictive control method for the steam generator water level
    • Na MG. Auto-tuned PID controller using a modelpredictive control method for the steam generator water level. IEEE Transactions on Nuclear Science 2001;48:1664-1671.
    • (2001) IEEE Transactions on Nuclear Science , vol.48 , pp. 1664-1671
    • Na, M.G.1
  • 5
    • 27644492927 scopus 로고    scopus 로고
    • Auto-tuning of PID controller parameters with supervised receding horizon optimization
    • Xu M, Li S, Qi C., Cai W. Auto-tuning of PID controller parameters with supervised receding horizon optimization. ISA Transactions 2005;44:491-500.
    • (2005) ISA Transactions , vol.44 , pp. 491-500
    • Xu, M.1    Li, S.2    Qi, C.3    Cai, W.4
  • 7
    • 0242695689 scopus 로고    scopus 로고
    • Applying neural networks to on-line updated PID controllers for nonlnear process control
    • Chen J, Huang T. Applying neural networks to on-line updated PID controllers for nonlnear process control. Journal of Process Control 2004;14:211-230.
    • (2004) Journal of Process Control , vol.14 , pp. 211-230
    • Chen, J.1    Huang, T.2
  • 9
    • 0032674115 scopus 로고    scopus 로고
    • Genetic tuning of PID controllers using a neural network model: A seesaw example
    • Wu C. Genetic tuning of PID controllers using a neural network model: a seesaw example. Journal of Intelligent and Robotic Systems 1999;25:43-59.
    • (1999) Journal of Intelligent and Robotic Systems , vol.25 , pp. 43-59
    • Wu, C.1
  • 14
    • 33751209792 scopus 로고    scopus 로고
    • Support vector machines-based generalized predictive control
    • Iplikci S. Support vector machines-based generalized predictive control. International Journal of Robust and Nonlinear Control 2006;16(17):843-862.
    • (2006) International Journal of Robust and Nonlinear Control , vol.16 , Issue.17 , pp. 843-862
    • Iplikci, S.1
  • 15
    • 33846087392 scopus 로고    scopus 로고
    • Online trained support vector machines-based generalized predictive control of non-linear systems
    • Iplikci S. Online trained support vector machines-based generalized predictive control of non-linear systems. International Journal of Adaptive Control and Signal Processing 2006;20(10):599-621.
    • (2006) International Journal of Adaptive Control and Signal Processing , vol.20 , Issue.10 , pp. 599-621
    • Iplikci, S.1
  • 16
    • 33745875609 scopus 로고    scopus 로고
    • Double inverted pendulum control based on support vector machines and fuzzy inference
    • Liu H, Wu H, Qian F. Double inverted pendulum control based on support vector machines and fuzzy inference. Proceeding of Advances in Neural Networks-ISNN 2006 2006;3972:1124-1130.
    • (2006) Proceeding of Advances in Neural Networks-ISNN 2006 , vol.3972 , pp. 1124-1130
    • Liu, H.1    Wu, H.2    Qian, F.3
  • 17
    • 34247580190 scopus 로고    scopus 로고
    • Support vector regression model predictive control on a hvac plant
    • Xi XC, Poo AN, Chou SK. Support vector regression model predictive control on a hvac plant. Control Engineering Practice 2007;15(8):897-908.
    • (2007) Control Engineering Practice , vol.15 , Issue.8 , pp. 897-908
    • Xi, X.C.1    Poo, A.N.2    Chou, S.K.3
  • 18
    • 33845972990 scopus 로고    scopus 로고
    • Online svm regression algorithm-based adaptive inverse control
    • Wang H, Pi D, Sun Y. Online svm regression algorithm-based adaptive inverse control. Neurocomputing 2007;70%(4-6):952-959.
    • (2007) Neurocomputing , vol.70 , Issue.4-6 , pp. 952-959
    • Wang, H.1    Pi, D.2    Sun, Y.3
  • 19
    • 47549085244 scopus 로고    scopus 로고
    • Self-tuning PID controller for a nonlinear system based on support vector machines
    • Liu H, Liu D. Self-tuning PID controller for a nonlinear system based on support vector machines. Kongzhi Lilun yu Yingyong/Control Theory and Applications 2008;25(3):468-474.
    • (2008) Kongzhi Lilun Yu Yingyong/Control Theory and Applications , vol.25 , Issue.3 , pp. 468-474
    • Liu, H.1    Liu, D.2
  • 24
    • 0003401675 scopus 로고    scopus 로고
    • A tutorial on support vector regression
    • Royal Holloway College, University of London
    • Smola AJ, Scholkopf B. A tutorial on support vector regression. NeuroCOLT Technical Report NC-TR-98-030, Royal Holloway College, University of London, 1998.
    • (1998) NeuroCOLT Technical Report NC-TR-98-030
    • Smola, A.J.1    Scholkopf, B.2
  • 28
    • 0032633127 scopus 로고    scopus 로고
    • A novel analysis and design of a neural network assisted nonlinear controller for a bioreactor
    • Efe MO, Abadoglu E, Kaynak O. A novel analysis and design of a neural network assisted nonlinear controller for a bioreactor. International Journal of Robust and Nonlinear Control 1999;9(11):799-815.
    • (1999) International Journal of Robust and Nonlinear Control , vol.9 , Issue.11 , pp. 799-815
    • Efe, M.O.1    Abadoglu, E.2    Kaynak, O.3
  • 29
    • 0344240878 scopus 로고    scopus 로고
    • Adaptive feedforward and feedback control of nonlinear time-varying uncertain systems
    • Wu W, Chou YS. Adaptive feedforward and feedback control of nonlinear time-varying uncertain systems. International Journal of Control 1999;72(12):1127-1138.
    • (1999) International Journal of Control , vol.72 , Issue.12 , pp. 1127-1138
    • Wu, W.1    Chou, Y.S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.