Path following and trajectory tracking model predictive control using artificial variables for constrained vehicles
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Universidade Federal de Minas Gerais
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In this article, the path following and trajectory tracking problems for constrained vehicles are tackled by means of a unified Model Predictive Control strategy. State and input constraints are taken into account, and additional artificial variables are included in the controller optimization problem to overcome several feasibility problems. To illustrate the performance of the approach we discuss the example of an autonomous vehicle subject to input constraints.
Abstract
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Teoria do controle, Sistemas não lineares
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Trajectory tracking , Trajectory , Optimal control , Predictive control , Numerical models , Predictive models , Conferences, nonlinear model predictive control , path following , trajectory tracking , artificial variables, Model Predictive Control , Artificial Variables , Optimization Problem , Autonomous Vehicles , Optimal Control Problem , Input Constraints , Trajectory Tracking Problem , Discretion , Nonlinear Model , Cost Function , Optimal Control , Control Input , Control Problem , Angular Velocity , Kind Of Problem , Coordinate Frame , Reference Trajectory , Skew-symmetric , Reference Input , Inertial Frame , Output Trajectory , Trajectory Path , Reference Output , Identically Zero , Input Trajectory , Constrained System , Sharp Turn , Spatial Path
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https://ieeexplore.ieee.org/document/8882189