Toward a Smart Car: Hybrid Nonlinear Predictive Controller With Adaptive Horizon

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F18%3A00479178" target="_blank" >RIV/67985556:_____/18:00479178 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TCST.2017.2747504" target="_blank" >http://dx.doi.org/10.1109/TCST.2017.2747504</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TCST.2017.2747504" target="_blank" >10.1109/TCST.2017.2747504</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Toward a Smart Car: Hybrid Nonlinear Predictive Controller With Adaptive Horizon

Popis výsledku v původním jazyce

This paper focuses on the development of an optimization algorithm for car motion predictive control that addresses both hybrid car dynamics and hybrid minimization criterion. Instead of solving computationally demanding nonlinear mixed-integer programming task or approximating the hybrid dynamics/criterion, the Hamiltonian-switching hybrid nonlinear predictive control algorithm developed in this paper incorporates the information about hybridity directly into the optimization routine. To decrease the time complexity, several adaptive prediction horizon approaches are proposed, and for some of them, it is shown that they preserve maneuverability-related properties of the car. All developed alternatives are verified on an example of a motion control of a racing car and compared with the approximation-based nonlinear predictive control and a commercial product. Moreover, a sensitivity analysis examining robustness of the algorithm is included as well.

Název v anglickém jazyce

Toward a Smart Car: Hybrid Nonlinear Predictive Controller With Adaptive Horizon

Popis výsledku anglicky

This paper focuses on the development of an optimization algorithm for car motion predictive control that addresses both hybrid car dynamics and hybrid minimization criterion. Instead of solving computationally demanding nonlinear mixed-integer programming task or approximating the hybrid dynamics/criterion, the Hamiltonian-switching hybrid nonlinear predictive control algorithm developed in this paper incorporates the information about hybridity directly into the optimization routine. To decrease the time complexity, several adaptive prediction horizon approaches are proposed, and for some of them, it is shown that they preserve maneuverability-related properties of the car. All developed alternatives are verified on an example of a motion control of a racing car and compared with the approximation-based nonlinear predictive control and a commercial product. Moreover, a sensitivity analysis examining robustness of the algorithm is included as well.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GA17-04682S" target="_blank" >GA17-04682S: Řízení kráčejících robotů metodou sladěných virtuálních holonomních omezení</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Control Systems Technology

ISSN

1063-6536

e-ISSN

—

Svazek periodika

26

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

1970-1981

Kód UT WoS článku

000447047900004

EID výsledku v databázi Scopus

2-s2.0-85030787288