The general stability theory of nonlinear receding horizon controllers has attracted much attention over the last fifteen years, and many algorithms have been proposed to ensure closed-loop stability. On the other hand many reports exist regarding the use of artificial neural network models in nonlinear receding horizon control. However, little attention has been given to the stability issue of these specific controllers. This paper addresses this problem and proposes to cast the nonlinear receding horizon control based on neural network models within the framework of an existing stabilising algorithm.
|Title of host publication||14th Mediterranean Conference on Control and Automation, 2006|
|Subtitle of host publication||MED '06|
|Place of Publication||Piscataway|
|Publication status||Published - 2006|
- RBF neural network model, closed-loop stability, nonlinear receding horizon controller, stabilisation algorithm, stability theory, stable nonlinear receding horizon regulator