Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot

In this paper, a stochastic model predictive control (MPC) is proposed for the wheeled mobile robot to track a reference trajectory within a finite task horizon. The wheeled mobile robot is supposed to subject to additive stochastic disturbance with known probability distribution. It is also suppose...

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Autores principales:	Weijiang Zheng, Bing Zhu
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	model predictive control mobile robot probability constraint linear time-varying systems optimization General Works A
Acceso en línea:	https://doaj.org/article/b28486ccdbd84be6aece8b050eb874be
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id	oai:doaj.org-article:b28486ccdbd84be6aece8b050eb874be
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spelling	oai:doaj.org-article:b28486ccdbd84be6aece8b050eb874be2021-11-18T09:18:41ZStochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot2296-598X10.3389/fenrg.2021.767597https://doaj.org/article/b28486ccdbd84be6aece8b050eb874be2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fenrg.2021.767597/fullhttps://doaj.org/toc/2296-598XIn this paper, a stochastic model predictive control (MPC) is proposed for the wheeled mobile robot to track a reference trajectory within a finite task horizon. The wheeled mobile robot is supposed to subject to additive stochastic disturbance with known probability distribution. It is also supposed that the mobile robot is subject to soft probability constraints on states and control inputs. The nonlinear mobile robot model is linearized and discretized into a discrete linear time-varying model, such that the linear time-varying MPC can be applied to forecast and control its future behavior. In the proposed stochastic MPC, the cost function is designed to penalize its tracking error and energy consumption. Based on quantile techniques, a learning-based approach is applied to transform the probability constraints to deterministic constraints, and to calculate the terminal constraint to guarantee recursive feasibility. It is proved that, with the proposed stochastic MPC, the tracking error of the closed-loop system is asymptotically average bounded. A simulation example is provided to support the theoretical result.Weijiang ZhengBing ZhuFrontiers Media S.A.articlemodel predictive controlmobile robotprobability constraintlinear time-varying systemsoptimizationGeneral WorksAENFrontiers in Energy Research, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	model predictive control mobile robot probability constraint linear time-varying systems optimization General Works A
spellingShingle	model predictive control mobile robot probability constraint linear time-varying systems optimization General Works A Weijiang Zheng Bing Zhu Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
description	In this paper, a stochastic model predictive control (MPC) is proposed for the wheeled mobile robot to track a reference trajectory within a finite task horizon. The wheeled mobile robot is supposed to subject to additive stochastic disturbance with known probability distribution. It is also supposed that the mobile robot is subject to soft probability constraints on states and control inputs. The nonlinear mobile robot model is linearized and discretized into a discrete linear time-varying model, such that the linear time-varying MPC can be applied to forecast and control its future behavior. In the proposed stochastic MPC, the cost function is designed to penalize its tracking error and energy consumption. Based on quantile techniques, a learning-based approach is applied to transform the probability constraints to deterministic constraints, and to calculate the terminal constraint to guarantee recursive feasibility. It is proved that, with the proposed stochastic MPC, the tracking error of the closed-loop system is asymptotically average bounded. A simulation example is provided to support the theoretical result.
format	article
author	Weijiang Zheng Bing Zhu
author_facet	Weijiang Zheng Bing Zhu
author_sort	Weijiang Zheng
title	Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
title_short	Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
title_full	Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
title_fullStr	Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
title_full_unstemmed	Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot
title_sort	stochastic time-varying model predictive control for trajectory tracking of a wheeled mobile robot
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/b28486ccdbd84be6aece8b050eb874be
work_keys_str_mv	AT weijiangzheng stochastictimevaryingmodelpredictivecontrolfortrajectorytrackingofawheeledmobilerobot AT bingzhu stochastictimevaryingmodelpredictivecontrolfortrajectorytrackingofawheeledmobilerobot
_version_	1718420922919026688

Stochastic Time-Varying Model Predictive Control for Trajectory Tracking of a Wheeled Mobile Robot

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