Self-triggered model predictive control for nonholonomic systems

Alina Eqtami, Shahab Heshmati-Alamdari, Dimos V. Dimarogonas, Kostas J. Kyriakopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper proposes a Model Predictive Control (MPC) framework combined with a self-triggering mechanism for constrained uncertain systems. Under the proposed scheme, the control input as well as the next control update time are provided at each triggering instant. Between two consecutive triggering instants, the control trajectory given by the MPC is applied to the plant in an open-loop fashion. This results to less frequent computations while preserving stability and convergence of the closed-loop system. A scenario for the stabilization of a nonholonomic robot subject to constraints and disturbances is considered, with the aim of reaching a specific triggering mechanism. The robot under the proposed control framework is driven to a compact set where it is ultimately bounded. The efficiency of the proposed approach is illustrated through a simulated example.

Original languageEnglish (US)
Title of host publication2013 European Control Conference, ECC 2013
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)9783033039629
StatePublished - 2013
Event2013 12th European Control Conference, ECC 2013 - Zurich, Switzerland
Duration: Jul 17 2013Jul 19 2013

Publication series

Name2013 European Control Conference, ECC 2013


Other2013 12th European Control Conference, ECC 2013

ASJC Scopus subject areas

  • Control and Systems Engineering


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