Title :
Nonlinear model predictive control using multi-model approach based on Fractal Dimension Measurement
Author :
Wenguang, Luo ; Hongli, Lan
Author_Institution :
Dept. of Electron. Inf. & Control Eng., Guangxi Univ. of Technol., Liuzhou, China
Abstract :
A nonlinear discrete time system can be locally linearized and represented by a multi-model structure, and model´s switching operation will affect system´s performances. A novel switching strategy is proposed to make the multi-model system satisfy the given performances, namely, fractal dimension measurement (shortened as FDM) of Euclid norms between working points and the equilibrium point acts as a criterion for switching. A model predictive control strategy based on Laguerre functions is designed to make each linear system optimize for a given cost function. The simulation results are presented to validate the method.
Keywords :
discrete time systems; nonlinear control systems; predictive control; time-varying systems; Euclid norms; Laguerre functions; fractal dimension measurement; model switching operation; multimodel structure; nonlinear discrete time system; nonlinear model predictive control; Control system synthesis; Control systems; Discrete time systems; Fractals; Nonlinear control systems; Nonlinear systems; Performance evaluation; Predictive control; Predictive models; Switches; Euclid norm; fractal dimension measurement; multi-model control; nonlinear system; switch control;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5358330
