System Modelling and Optimization under Vector-Valued Criteria

The integrated system optimization and parameter estimation problem is addressed in the context of vector-valued optimization techniques. The validity of the existing convergence properties of the basic two-step approach for solving the joint problem of scalar optimization and parameter estimation is extended for the vector-valued case under appropriate conditions. Some elements of decision analysis are incorporated into the integrated optimization and parameter estimation scheme in order to reflect conflicting situations derived from the simultaneous consideration of multiple performance criteria. To illustrate the main aspects of the proposed approach, the joint problem of optimization and parameter estimation of a nonlinear dynamic batch reactor is considered.

[1]  P. D. Roberts,et al.  Newton-like algorithm for integrated system optimization and parameter estimation technique , 1987 .

[2]  Arthur M. Geoffrion,et al.  Solving Bicriterion Mathematical Programs , 1967, Oper. Res..

[3]  P. D. Roberts,et al.  An algorithm for steady-state system optimization and parameter estimation , 1979 .

[4]  Dale E. Seborg,et al.  A contemplative stance for chemical process control , 1987 .

[5]  Yacov Y. Haimes,et al.  Parametric solution to the joint system identification and optimization problem , 1974 .

[6]  Yacov Y. Haimes,et al.  A computational approach to the combined problem of optimization and parameter identification , 1972 .

[7]  J. Cohon,et al.  Generating multiobjective trade-offs: an algorithm for bicriterion problems , 1979 .

[8]  K. Denbigh,et al.  Chemical Reactor Theory: an Introduction , 1965 .

[9]  Alan S. Foss,et al.  Critique of chemical process control theory , 1973 .

[10]  Elijah Polak,et al.  An algorithm for bicriteria optimization based on the sensitivity function , 1975 .

[11]  William L. Luyben,et al.  Process Modeling, Simulation and Control for Chemical Engineers , 1973 .

[12]  Yacov Y. Haimes,et al.  On the characterization of noninferior solutions of the vector optimization problem , 1982, Autom..

[13]  Yacov Y. Haimes,et al.  Risk/dispersion index method , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  M. Brdys,et al.  Optimal structures for steady-state adaptive optimizing control of large-scale industrial processes , 1986 .

[15]  E. Polak,et al.  An algorithm for bicriteria optimization based on the sensitivity function , 1974, CDC 1974.

[16]  G. J. Vachtsevanos Lpconvergence of a process identification algorithm , 1975 .

[17]  José Claudio Geromel,et al.  An interactive projection method for multicriteria optimization problems , 1990, IEEE Trans. Syst. Man Cybern..

[18]  Bill Curtis,et al.  Process modeling , 1992, CACM.