Autonomous ground vehicle lane-keeping LPV model-based control : Dual-rate state estimation and comparison of different real-time control strategies

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Salt Ducajú, Julián M.Lund University,Lunds universitet,Institutionen för reglerteknik,Institutioner vid LTH,Lunds Tekniska Högskola,Department of Automatic Control,Departments at LTH,Faculty of Engineering, LTH (author)

Autonomous ground vehicle lane-keeping LPV model-based control : Dual-rate state estimation and comparison of different real-time control strategies

Article/chapterEnglish2021

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2021-02-23
MDPI AG,2021
17 s.

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LIBRIS-ID:oai:lup.lub.lu.se:d1829a82-144e-45aa-91d4-0149c70204db
https://lup.lub.lu.se/record/d1829a82-144e-45aa-91d4-0149c70204dbURI
https://doi.org/10.3390/s21041531DOI

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Language:English
Summary in:English

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SwePubSwePub

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Subject category:art swepub-publicationtype
Subject category:ref swepub-contenttype

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In this contribution, we suggest two proposals to achieve fast, real-time lane-keeping control for Autonomous Ground Vehicles (AGVs). The goal of lane-keeping is to orient and keep the vehicle within a given reference path using the front wheel steering angle as the control action for a specific longitudinal velocity. While nonlinear models can describe the lateral dynamics of the vehicle in an accurate manner, they might lead to difficulties when computing some control laws such as Model Predictive Control (MPC) in real time. Therefore, our first proposal is to use a Linear Parameter Varying (LPV) model to describe the AGV’s lateral dynamics, as a trade-off between computational complexity and model accuracy. Additionally, AGV sensors typically work at different measurement acquisition frequencies so that Kalman Filters (KFs) are usually needed for sensor fusion. Our second proposal is to use a Dual-Rate Extended Kalman Filter (DREFKF) to alleviate the cost of updating the internal state of the filter. To check the validity of our proposals, an LPV model-based control strategy is compared in simulations over a circuit path to another reduced computational complexity control strategy, the Inverse Kinematic Bicycle model (IKIBI), in the presence of process and measurement Gaussian noise. The LPV-MPC controller is shown to provide a more accurate lane-keeping behavior than an IKIBI control strategy. Finally, it is seen that Dual-Rate Extended Kalman Filters (DREKFs) constitute an interesting tool for providing fast vehicle state estimation in an AGV lane-keeping application.

Subject headings and genre

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Reglerteknik hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Control Engineering hsv//eng
TEKNIK OCH TEKNOLOGIER Maskinteknik Farkostteknik hsv//swe
ENGINEERING AND TECHNOLOGY Mechanical Engineering Vehicle Engineering hsv//eng
Autonomous vehicle
Dual-rate control
Dual-rate EKF
LPV model
MPC

Added entries (persons, corporate bodies, meetings, titles ...)

Llobregat, Julián J.SaltPolytechnic University of Valencia (author)
Cuenca, ÁngelPolytechnic University of Valencia (author)
Tomizuka, MasayoshiUniversity of California, Berkeley (author)
Institutionen för reglerteknikInstitutioner vid LTH (creator_code:org_t)

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In:Sensors: MDPI AG21:41424-8220

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ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...; and Control Engineer ...

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