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Nonlinear Model Predictive Controller and Feasible Path Planning for Autonomous Robots

Nonlinear Model Predictive Controller and Feasible Path Planning for Autonomous Robots AbstractThis paper develops the nonlinear model predictivecontrol (NMPC) algorithm to control autonomousrobots tracking feasible paths generated directly from thenonlinear dynamic equations.NMPC algorithm can securethe stability of this dynamic system by imposing additionalconditions on the open loop NMPC regulator. TheNMPC algorithm maintains a terminal constrained regionto the origin and thus, guarantees the stability of the nonlinearsystem. Simulations show that the NMPC algorithmcan minimize the path tracking errors and control the autonomousrobots tracking exactly on the feasible pathssubject to the system’s physical constraints. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Open Computer Science de Gruyter

Nonlinear Model Predictive Controller and Feasible Path Planning for Autonomous Robots

Minh, Vu Trieu
Open Computer Science , Volume 6 (1): 9 – Jan 1, 2016
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Publisher
de Gruyter
Copyright
© 2016 Vu Trieu Minh
eISSN
2299-1093
DOI
10.1515/comp-2016-0015
Publisher site
See Article on Publisher Site

Abstract

AbstractThis paper develops the nonlinear model predictivecontrol (NMPC) algorithm to control autonomousrobots tracking feasible paths generated directly from thenonlinear dynamic equations.NMPC algorithm can securethe stability of this dynamic system by imposing additionalconditions on the open loop NMPC regulator. TheNMPC algorithm maintains a terminal constrained regionto the origin and thus, guarantees the stability of the nonlinearsystem. Simulations show that the NMPC algorithmcan minimize the path tracking errors and control the autonomousrobots tracking exactly on the feasible pathssubject to the system’s physical constraints.

Journal

Open Computer Science – de Gruyter

Published: Jan 1, 2016

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