Please use this identifier to cite or link to this item:
|Title:||Constrained Non-linear Model Based Predictive Control using Genetic Algorithms|
|Abstract:||Model based predictive control (MBPC) is one of the most powerful techniques in process control, however, two main problems need to be considered : obtaining a suitable nonlinear model and an efficient optimization procedure. In this paper, non-linear models are used to predict the plant future response. A genetic algorithm based approach is then used in an MBPC structure to deal with the problem of optimisation which is non convex and thus difficult to solve. The efficiency of this approach had been demonstrated with simulation examples.|
|Appears in Collections:||Communications Internationales|
Files in This Item:
|“Constrained Non Linear Model Based Predictive Control using Genetic Algorithms”,.pdf||179,87 kB||Adobe PDF||View/Open|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.