Autonomous Vehicle Tracking Based on Non-Linear Model Predictive Control Approach

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F22%3A00010092" target="_blank" >RIV/46747885:24220/22:00010092 - isvavai.cz</a>
Alternative codes found
RIV/46747885:24620/22:00010092
Result on the web
<a href="https://www.igi-global.com/chapter/autonomous-vehicle-tracking-based-on-non-linear-model-predictive-control-approach/302063" target="_blank" >https://www.igi-global.com/chapter/autonomous-vehicle-tracking-based-on-non-linear-model-predictive-control-approach/302063</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4018/978-1-7998-9012-6.ch005" target="_blank" >10.4018/978-1-7998-9012-6.ch005</a>

Result language
angličtina
Original language name
Autonomous Vehicle Tracking Based on Non-Linear Model Predictive Control Approach
Original language description
Autonomous driving vehicles are developing rapidly; however, the control systems for autonomous driving vehicles tracking smoothly in high speed are still challenging. This chapter develops non-linear model predictive control (NMPC) schemes for controlling autonomous driving vehicles tracking on feasible trajectories. The optimal control action for vehicle speed and steering velocity is generated online using NMPC optimizer subject to vehicle dynamic and physical constraints as well as the surrounding obstacles and the environmental side-slipping conditions. NMPC subject to softened state constraints provides a better possibility for the optimizer to generate a feasible solution as real-time subject to online dynamic constraints and to maintain the vehicle stability. Different parameters of NMPC are simulated and analysed to see the relationships between the NMPC horizon prediction length and the weighting values. Results show that the NMPC can control the vehicle tracking exactly on different trajectories with minimum tracking errors and with high comfortability.
Czech name
—
Czech description
—

Project
<a href="/en/project/EF16_025%2F0007293" target="_blank" >EF16_025/0007293: Modular platform for autonomous chassis of specialized electric vehicles for freight and equipment transportation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Applications of Computational Science in Artificial Intelligence
ISBN
978-1799890140
Number of pages of the result
58
Pages from-to
74-131
Number of pages of the book
284
Publisher name
IGI Global
Place of publication
—
UT code for WoS chapter
—

Similar results(10)