Optimization of temporal processes: A model predictive control approach
IEEE Transactions on Evolutionary Computation
A dynamic predictive-control model of a nonlinear and temporal process is considered. Evolutionary computation and data mining algorithms are integrated for solving the model. Data-mining algorithms learn dynamic equations from process data. Evolutionary algorithms are then applied to solve the optimization problem guided by the knowledge extracted by data-mining algorithms. Several properties of the optimization model are shown in detail, in particular, a selection of regressors, time delays, prediction and control horizons, and weights. The concepts proposed in this paper are illustrated with an industrial case study in combustion process. 2008 IEEE.
Published Article/Book Citation
IEEE Transactions on Evolutionary Computation, 13:1 (2009) pp.169-179.
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