Abstract

A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

주제어

#Predictive control   #parametric optimization   #multi-objective optimization  

참고문헌 (29)

1. A multi-objective design algorithm: Application to the design of SISO control systems , A. Abbas;P. Sawyer , Computers Chem. Engng. / v.19,pp.241-248, 1995
   
2. On linear programming and robust model predictive control using impulse-responses , J. Allwright;G. Papavasiliou , System and Control Letters / v.18,pp.159-164, 1992
   
3. Robust model predictive control of stable linear systems , T. Badgwell , International Journal of Control / v.68,pp.797-818, 1997
   
4. Reducing conservativeness in predictive control of constrained system with disturbances , A. Bemporad , Proc. 37th IEEE Conference on Decision and Control / v.,pp.2133-2138, 1998
   
5. Robust model predictive control , P. Campo;M. Morari , Proc. American Contr. Conf. / v.,pp.1021-1026, 1987
   
6. V. Chankong;Y. Haimes , Multiobjective Decision Making: Theory and Methodology / v.,pp., 1983
   
7. C. Desoer;M. Vidyasagar , Feedback System: Input-Output Properties / v.,pp., 1975
   
8. On efficient sets in vector maximum problems-A brief survey , T. Gal , European Journal of Operational Research / v.24,pp.253-264, 1986
   
9. Model predictive control: Theory and practice.A survey , C. Garcia;D. M. Prett;M. Morari , Automatica / v.25,pp.335-348, 1989
   
10. Linear systems with state and control constraints: The theory and application of maximal output admissible , E. Gilbert;K. Tan , IEEE Trans. Autom. Contr. / v.36,pp.1008-1019, 1991
    
11. Maximal output admissible sets for discrete-time systems with disturbance inputs , E. Gilbert;I. Kolmanovsky , Proc. of the American Contr. Conf. / v.,pp.2000-2005, 1995
    
12. Shaping timedomain response with discrete controllers , L. Giovanini;J. Marchetti , Ind. Eng. Chem. Res. / v.38,pp.4777-4789, 1999
    
13. Predictive feedback control , L. Giovanini , ISA Transaction Journal / v.42,pp.207-226, 2003
    
14. Robust constrained model predictive control using linear matrix inequalities , M. V. Kothare;V. Balakrishanan;M. Morari , Automatica / v.32,pp.1361-1379, 1996
    
15. Linear quadratic feasible predictive control , B. Kouvaritakis;J. Rossiter;Cannon, M. , Automatica / v.34,pp.1583-1592, 1998
    
16. Efficient robust predictive control , B. Kouvaritakis;A. Rossiter;J. Schuurmans , IEEE Trans. Autom. Contr. / v.45,pp.1545-1549, 2000
    
17. Tuning of model predictive controllers for robust performance , J. Lee;Z. Yu , Computers Chem. Engng. / v.18,pp.15-37, 1994
    
18. Worst-case formulation of model predictive control for system with bounded parameters , J. Lee;Z. Yu , Automatica / v.33,pp.763-781, 1997
    
19. A contraction property for state feedback design of linear discrete-time systems , A. Malmgrem;A. Nordstrom , Automatica / v.30,pp.1485-1489, 1994
    
20. Receding horizon control of nonlinear systems , D. Mayne;E. Michalska , IEEE Trans. Autom. Contr. / v.35,pp.814-824, 1990
    
21. Predictive controller design by principal component analysis , P. Maurath;A. Laub;D. Seborg;D. Mellichamp , Ind. Eng. Chem. Res. / v.27,pp.1204-1212, 1988
    
22. An adaptive nonlinear predictive controller , J. Morningred;B. Paden;D. Seborg;D. Mellichamp , Chem. Eng. Sci. / v.47,pp.755-765, 1992
    
23. Constrained linear quadratic regulation , P. Scokaert;J. Rawlings , IEEE Trans. Autom. Contr. / v.43,pp.1163-1169, 1998
    
24. Y. Sawaragi;H. Nakayama;T. Tanino , Theory of Multiobjective Optimization / v.,pp., 1985
    
25. P. Van Overschee;B. De Moor , Subspace Identification for Linear System / v.,pp., 1996
    
26. Performance bounds for robust quadratic dynamic matrix control with end condition , P. Vuthandam;H. Genceli;M. Nikolaou , AICHE / v.41,pp.2083-2097, 1995
    
27. Robust model predictive control with hard constraints , E. Zafiriou , Computers Chem. Engng. / v.14,pp.359-371, 1990
    
28. Stability of model predictive control with mixed constraints , Z. Zheng;M. Morari , IEEE Trans. on Automatic Control / v.40,pp.1818-1823, 1995
    
29. Robust stability analysis of constrained l1-norm model predictive control , H. Genceli;M. Nikolaou , AIChE J. / v.39,pp.1954-1965, 1993
    

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