Title :
Design of an analytic constrained predictive controller using neural networks
Author :
Hoekstra, Peter ; van den Boom, Ton J. J. ; Ayala Botto, Miguel
Author_Institution :
Dept. Inf. Technol. & Syst., Delft Univ. of Technol., Delft, Netherlands
Abstract :
The solution to the standard predictive control problem is a continuous function of the state, the reference signal, the noise and the disturbances and hence can be approximated arbitrarily close by a feed-forward neural network. This leads to an analytic constrained predictive controller that combines constraint handling with speed and is applicable to fast systems and complex control problems with many constraints.
Keywords :
continuous systems; control system synthesis; feedforward neural nets; neurocontrollers; predictive control; analytic constrained predictive controller design; complex control problems; constraint handling; continuous function; feed-forward neural network; standard predictive control problem; Elevators; Neural networks; Noise; Optimization; Predictive control; Standards; Control and Optimization; Control of Systems with Input Non-linearities; Neural Networks; Predictive Control; Signal Constraints;
Conference_Titel :
Control Conference (ECC), 2001 European
Conference_Location :
Porto
Print_ISBN :
978-3-9524173-6-2
