Title :
Model based predictive control: an extended state space approach
Author :
Ruscio, David Di
Author_Institution :
Telemark Inst. of Technol., Porsgrunn, Norway
Abstract :
An extended state space (ESS) model, familiar in subspace identification theory, is used for the development of a model based predictive control algorithm for linear model structures. In the ESS model, the state vector consists of system outputs, which eliminates the need for a state estimator. A framework for model based predictive control is presented. Both general linear state space model structures and finite impulse response models fit into this framework
Keywords :
discrete time systems; identification; linear systems; matrix algebra; optimal control; predictive control; state-space methods; discrete time systems; extended state space model; finite impulse response; linear model; linear systems; model based predictive control; optimal control; state transition matrix; subspace identification; Ear; Electronic switching systems; Prediction algorithms; Predictive control; Predictive models; Riccati equations; Space technology; State estimation; State-space methods; Vectors;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.652337
