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Optimisation of lateral car dynamics taking into account parameter uncertainties.

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Název: Optimisation of lateral car dynamics taking into account parameter uncertainties.
Autoři: Busch, Jochen, Bestle, Dieter
Zdroj: Vehicle System Dynamics; Feb2014, Vol. 52 Issue 2, p166-185, 20p
Témata: MOTOR vehicle dynamics, MOTOR vehicle steering gear, ROBUST control, GENETIC algorithms, PARAMETER estimation, UNCERTAINTY (Information theory), LATIN hypercube sampling, SIMULATION methods & models
Abstrakt: Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure. [ABSTRACT FROM PUBLISHER]
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Databáze: Complementary Index
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Abstrakt:Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure. [ABSTRACT FROM PUBLISHER]
ISSN:00423114
DOI:10.1080/00423114.2013.868006