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Estimating Real Process Derivatives in on-Line Optimization - A Review

Abstract: The solution of the Integrated System Optimization and Parameter Estimation (ISOPE) problem necessitates the calculus of real process output derivatives with respect to the inputs. This information is needed in order to satisfy first and second order optimality conditions. Several methods exist and have been developed for calculating these derivatives. In this paper a review of most of the existing methods is presented, in which the Finite Difference Approximation, Dual Control Optimization, Broydon’s method, Dynamic Model Identification, with both linear and nonlinear models, together with a neural networks scheme are presented and applied, under simulation, to a cascade Continuous Stirred Tank Reactor (CSTR) system. The results are then discussed and compared to identify the advantages and disadvantages of using each method.