A MIN-MAX PREDICTIVE CONTROL ALGORITHM FOR UNCERTAIN NORM-BOUNDED LINEAR SYSTEMS
Alessandro Casavola* Domenico Famularo** Giuseppe Franzè*
* DEIS - Università degli studi della Calabria, Rende(CS), 87036 ITALY, {casavola, franze}@deis.unical.it
** ISI - Consiglio Nazionale delle Ricerche, Rende (CS) 87036, ITALY, famularo@isi.cs.cnr.it
A novel robust predictive control algorithm for input-saturated uncertain linear discrete-time systems with structured norm-bounded uncertainties is presented. The solution is based on the minimization, at each time instant, of a LMI convex optimization problem obtained by a recursive use of the S-procedure. The general case of N free moves is presented. Stability and feasibility are proved and comparisons with robust multi-model (polytopic) MPC algorithms are also presented via an example.
Keywords: Uncertain linear systems, Predictive control, Constraint satisfaction problems, Convex programming, Minimax techniques
Session slot T-We-A17: Predictive Control/Area code 2e : Robust Control

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