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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Stationary policies for lower bounds on the minimum average cost of discrete-time nonlinear control systems

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Author(s):
Vargas, Alessandro N. [1, 2] ; Ishihara, Joao Y. [2, 3] ; do Val, Joao B. R. [4]
Total Authors: 3
Affiliation:
[1] Univ Tecnol Fed Parana, UTFPR, BR-86300000 Cornelio Procopio, PR - Brazil
[2] BCAM, E-48009 Bilbao, Vizcaya - Spain
[3] Univ Brasilia, UnB, FT, BR-70910900 Brasilia, DF - Brazil
[4] Univ Estadual Campinas, UNICAMP, FEEC DT, BR-13083852 Campinas, SP - Brazil
Total Affiliations: 4
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL; v. 24, n. 17, p. 2943-2957, NOV 25 2014.
Web of Science Citations: 0
Abstract

The paper deals with the control problem of discrete-time nonlinear systems. The main contribution of this note is to present conditions that assure the existence of stationary policies that generate lower bounds for the minimal long-run average cost. These lower bounds coincide with the optimal solution when a mild convergence assumption holds. To illustrate the results, the paper presents an application for the simultaneous state-feedback control problem, and the derived strategy is used to design a real-time simultaneous control for two direct current motor devices. The dynamics of these two devices are written in terms of a nonlinear algebraic matrix recurrence, which in turn represents a particular case for our general nonlinear approach. The optimal gain for the corresponding simultaneous state-feedback problem is obtained, and such a gain was implemented in a laboratory testbed to control simultaneously the two direct current motors. Copyright (c) 2013 John Wiley \& Sons, Ltd. (AU)

FAPESP's process: 03/06736-7 - Control and filtering of Markovian jumping parameters stochastic systems
Grantee:João Bosco Ribeiro do Val
Support type: Research Projects - Thematic Grants