Gain scheduled continuous-time model predictive controller with experimental validation on AC machine

References

• Allgower , F. and Zheng , A. , eds. 2000 . Nonlinear model predictive control: Volume 26 of progress in systems and control theory , Birkhauser Basel .
   Google Scholar
• Athans , M. , Castanon , D. , Dunn , K. , Greene , C. S. , Lee , W. H. , Sandell , N. R. and Willsky , A. S . 1977 . The stochastic control of the f-8c aircraft using a multiple model adaptive control method-part i: equilibrium flight . IEEE Transaction on Automatic Control , 22 : 768 – 780 . doi: 10.1109/TAC.1977.1101599
   Web of Science ®Google Scholar
• Bay , J. S . 1999 . Fundamentals of linear state space systems , McGraw-Hill .
   Google Scholar
• Bocker , J. and Mathapati , S. 2007 . “ State of the art of induction motor control ” . In Paper presented at Electric Machines and Drives Conference, 2007 , 1459 – 1464 . Antalya , , Turkey : IEEE International .
   Google Scholar
• Brand , M. , Shilpiekandula , V. , Yao , C. , Bortoff , S. A. , Nishiyama , T. , Yoshikawa , S. and Iwasaki , T. 2011 . “ A parallel quadratic programming algorithm for model predictive control ” . In Proceedings of the 18th IFAC World Congress Milan , , Italy
   Google Scholar
• Clarke , D. W. , Mohtadi , C. and Tuffs , P. S . 1987 . Generalized predictive control. Part 1: The basic algorithm. Part 2: Extensions and interpretations . Automatica , 23 : 137 – 160 . doi: 10.1016/0005-1098(87)90087-2
   Web of Science ®Google Scholar
• Desoer , C. A . 1969 . Slowly varying system . IEEE Transactions on Automatic Control , 14 : 780 – 781 . doi: 10.1109/TAC.1969.1099336
   Web of Science ®Google Scholar
• Dougherty , D. and Cooper , D . 2002 . A practical multiple model adaptive strategy for single-loop mpc . Control Engineering Practice , 11 : 141 – 159 . doi: 10.1016/S0967-0661(02)00106-5
   Web of Science ®Google Scholar
• Filho , E. R. and Souza , R. M. 1997 . “ Three-phase induction motor dynamic mathematical model ” . In IEEE International Electric Machines and Derives Conference Record MB1/2.1. Milwaukee, WI , , USA
   Google Scholar
• Nieto , S. , Martinez , M. , Blasco , X. and Sanchis , J . 2008 . Nonlinear model predictive control based on local model networks for air management in diesel engines . Control Engineering Practice , 16 : 1399 – 1413 . doi: 10.1016/j.conengprac.2008.03.010
   Web of Science ®Google Scholar
• Goodwin , G. C. , Graebe , S. and Salgado , M. 2000 . Control system design , Englewood Cliffs , , NJ : Prentice-Hall .
   Google Scholar
• 1998 . Nonlinear model predictive control: Current status and future directions . Computers and Chemical Engineering , 23, : 187 – 202 . doi: 10.1016/S0098-1354(98)00260-9
   Web of Science ®Google Scholar
• Holtz , J . 1994 . “ The induction motor–A dynamic system ” . In The 20th International Conference on Industrial Electronics, Control and Instrumentation Vol. 1 , P1 Bologna , , Italy
   Google Scholar
• 2010 . Model-based predictive control of electric drives , Cuvillier Verlag Gottingen .
   Google Scholar
• Maciejowski , J. M . 2002 . Predictive control with constraints , Upper Saddle River , , NJ : Pearson Education Limited .
   Google Scholar
• Narendra , K. S. and Balakrishnan , J . 1997 . Adaptive control using multiple models . IEEE Transaction on Automatic Control , 42 : 171 – 187 . doi: 10.1109/9.554398
   Web of Science ®Google Scholar
• Ozkan , L. , Kothare , M. V. and Georgakis , C. 2003 . Control of a solution copolymerization reactor using multi-model predictive control . Chemical Engineering Science , 58 : 1207 – 1221 . doi: 10.1016/S0009-2509(02)00559-6
   Web of Science ®Google Scholar
• Parfirio , C. R. , Neto , E. and Odloak , D . 2003 . Multi-model predictive control of an industrial c3/c4 splitter . Control Engineering Practice , 11 : 765 – 779 . doi: 10.1016/S0967-0661(02)00183-1
   Web of Science ®Google Scholar
• Quang , N. P. and Dittrich , J. -A. 2008 . Vector control of three-phase AC machines , 1st ed. , New York : Springer .
   Google Scholar
• Rawlings , J. B . 2000 . Tutorial overview of model predictive control . IEEE Control Systems Magazine , 20 : 38 – 52 . doi: 10.1109/37.845037
   Web of Science ®Google Scholar
• Rossiter , J. A . 2003 . Model-based predictive control, a practical approach , Prentice Hall Int .
   Google Scholar
• Rugh , W. J. 1991 . Analytical framework for gain scheduling . IEEE Control System Magazine , 12 : 35 – 49 .
   Google Scholar
• Rugh , W. J. and Shamma , J. S . 2000 . Research on gain scheduling . Automatica , 36 : 1401 – 1425 . doi: 10.1016/S0005-1098(00)00058-3
   Web of Science ®Google Scholar
• Shamma , J. S. and Athans , M . 1990 . Analysis of gain scheduled control for nonlinear plants . IEEE Transactions on Automatic Control , 35 : 898 – 907 . doi: 10.1109/9.58498
   Web of Science ®Google Scholar
• Stein , G. , Hartmann , G. and Hendrick , R. C . 1977 . Adaptive control laws for f-8 flight test . IEEE Transaction on Automatic Control , : 758 – 767 . doi: 10.1109/TAC.1977.1101605
   Web of Science ®Google Scholar
• Wan , Z. and Kothare , M. V . 2003 . Efficient scheduled stabilizing model predictive control for constrained nonlinear systems . International Journal of Robust and Nonlinear Control , 13 : 331 – 346 . doi: 10.1002/rnc.821
   Web of Science ®Google Scholar
• Wang , L . 2001 . Continuous time model predictive control using orthonormal functions . International Journal of Control , 74 : 1588 – 1600 . doi: 10.1080/00207170110082218
   Web of Science ®Google Scholar
• Wang , L. 2009 . Model predictive control system design and implementation using MATLAB , 1st ed. , Springer .
   Google Scholar
• Wang , Y. and Boyd , S. 2010 . Fast model predictive control using online optimization . IEEE Transactions on Control System Technology , 18 : 267 – 278 . doi: 10.1109/TCST.2009.2017934
   Web of Science ®Google Scholar