Can I read Genetic Algorithms for Optimization in Predictive Control on EtoBox?

Genetic Algorithms for Optimization in Predictive Control by C. Onnen; R. Babuška; U. Kaymak; J.M. Sousa; H.B. Verbruggen; R. Isermann is a Engineering article available to read on EtoBox.

What is Genetic Algorithms for Optimization in Predictive Control about?

Genetic algorithms (GAs) are optimization methods inspired by natural biological evolution. GAs have been successfully applied to a variety of complex optimization problems where other techniques have often failed. The aim of this paper is to investigate the use of GAs for optimization in nonlinear model-based predictive control. Advanced genetic operators and other new. features are introduced to increase the efficiency of the genetic search. In order to deal with real-time constraints, termination conditions are proposed to abort the evolution, once a defined level of optimality is reached. Simulated pressure dynamics of a batch fermenter are considered as an example of a highly nonlinear system. Simulation results with GAs are compared with the branch-and-bound method, in terms of the control accuracy and computational costs achieved.

Who reads Genetic Algorithms for Optimization in Predictive Control?

Author

C. Onnen; R. Babuška; U. Kaymak; J.M. Sousa; H.B. Verbruggen; R. Isermann

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0967-0661)

Published

1997

Language

EN

Field

Engineering (Physical Sciences)