Declercq, Filip ; Keyser, Robin de
Suboptimal nonlinear predictive controllers
Group publication title:
Subject and Keywords:
predictive control ; nonlinear control ; sequential quadratic programming ; diophantine equations
Predictive control based on linear models has become a mature technology in the last decade. Many successful real-time applications can be found in almost every sector of industry. Nonlinear predictive control can further increase the performance of this easy-to-understand control strategy. ; One of the main problems of implementing nonlinear predictive control is the computational aspect, which is of most importance in real-life applications. In this paper, suboptimal nonlinear predictive control strategies are proposed and compared. The nonlinear predictors are built based on neural identification methods or by white modelling. ; The use of diophantine equations, which is a common technique to calculate the optimal contribution of the noise model, is avoided by using a more natural method. The comparison between the control algorithms is made based on a simulated discrete multivariable nonlinear system and a continuous stirred tank reactor.
Zielona Góra: Uniwersytet Zielonogórski
AMCS, volume 9, number 1 (1999) ; click here to follow the link