© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; This study presents a solution for the integrated longitudinal and lateral control problem of urban autonomousvehicles. It is based on a gain-scheduling linear parameter-varying (LPV) control approach combined with the use of anUnknown Input Observer (UIO) for estimating the vehicle states and friction force. Two gain-scheduling LPV controllers are usedin cascade configuration that use the kinematic and dynamic vehicle models and the friction and observed states provided bythe Unknown Input Observer (UIO). The LPV–UIO is designed in an optimal manner by solving a set of linear matrix inequalities(LMIs). On the other hand, the design of the kinematic and dynamic controllers lead to solve separately two LPV–LinearQuadratic Regulator problems formulated also in LMI form. The UIO allows to improve the control response in disturbanceaffected scenarios by estimating and compensating the friction force. The proposed scheme has been integrated with atrajectory generation module and tested in a simulated scenario. A comparative study is also presented considering the casesthat the friction force estimation is used or not to show its usefulness ; Peer Reviewed ; Postprint (author's final draft)
Gain-scheduling LPV control for autonomous vehicles including friction force estimation and compensation mechanism
2018-08-14
Article (Journal)
Electronic Resource
English
Àrees temàtiques de la UPC::Informàtica::Robòtica , closed loop systems , control system synthesis , friction , linear matrix inequalities , linear quadratic control , linear systems , mobile robots , nonlinear control systems , observers , road vehicles , robot dynamics , robot kinematics , robust control , Classificació INSPEC::Automation::Robots
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