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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.)

On the use of mixed-integer linear programming for predictive control with avoidance constraints

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Author(s):
Maia, Marcelo H. ; Galvao, Roberto K. H. [1]
Total Authors: 2
Affiliation:
[1] Inst Tecnol Aeronaut, CTA, Div Engn Eletron, BR-12228900 Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 1
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL; v. 19, n. 7, p. 822-828, MAY 10 2009.
Web of Science Citations: 13
Abstract

This technical note concerns the predictive control of discrete-time linear models subject to state, input and avoidance polyhedral constraints. Owing to the presence of avoidance constraints, the optimization associated with the predictive control law is non-convex, even though the constraints themselves are convex. The inclusion of the avoidance constraints in the predictive control law is achieved by the use of a modified version of a mixed-integer programming approach previously derived in the literature. The proposed modification consists of adding constraints to ensure that linear segments of the system trajectories between consecutive sampling times do not cross existing obstacles. This avoids the significant extra computation that would be incurred if the sampling time was reduced to prevent these crossings. Simulation results show that the inclusion of these additional constraints successfully prevents obstacle collisions that would otherwise occur. Copyright (C) 2008 John Wiley \& Sons, Ltd. (AU)

FAPESP's process: 06/58850-6 - Diagnosis, prognosis and fault accommodation for dynamical systems
Grantee:Takashi Yoneyama
Support Opportunities: Research Projects - Thematic Grants