Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Predictive control of convex polyhedron LPV systems with Markov jumping parameters|
|Citation:||Proceedings of the 2012 24th Chinese Control and Decision Conference, CCDC 2012, 2012 / pp.603-608|
|Conference Name:||24th Chinese Control and Decision Conference (CCDC) (23 May 2012 - 25 May 2012 : Taiyuan, China)|
|Yin Yanyan, Liu Fei, Shi Peng, Karimi Hamid Reza|
|Abstract:||The problem of receding horizon predictive control of stochastic linear parameter varying systems is discussed. First, constant coefficient matrices are obtained at each vertex in the interior of linear parameter varying system, and then, by considering semi-definite programming constraints, weight coefficients between each vertex are calculated, and the equal coefficients matrices for the time variable system are obtained. Second, in the given receding horizon, for each mode sequence of the stochastic convex polyhedron linear parameter varying systems, the optimal control input sequences are designed in order to make the states into a terminal invariant set. Outside of the receding horizon, stability of the system is guaranteed by searching a state feedback control law. Finally, receding horizon predictive controller is designed in terms of linear matrix inequality for such system. Simulation example shows the validity of this method.|
|Keywords:||Predictive control; convex polyhedron; linear parameter varying systems; Markov jumping parameters|
|Appears in Collections:||Electrical and Electronic Engineering publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.