Multi-Objective Optimization of Nonlinear Controller for Untripped Rollover Prevention of an 8-dof Vehicle Dynamic Model

Abstract:

The pareto optimal controller design on a two-track vehicle dynamic model with 8-degrees of freedom considering two simultaneous conflicting objective functions has been made in order to prevent the rollover phenomena. In this regard, the requisiteness of trading off among the conflicting requirements of vehicle dynamic control results in utilizing multi-objective optimization techniques. More effectively, a multi-objective uniform-diversity genetic algorithm (MUGA) with a diversity preserving mechanism known as the ε-elimination algorithm has been used to optimize multi input multi output (MIMO) sliding mode controller. The most important conflicting objective functions that have been considered for minimization in this study are, control effort and vehicle roll angle, correspondingly. Finally, The comparison of the obtained results with those in the literature demonstrates that the strategy employed cause remarkable improvement in rollover prevention and maneuverability.

• Periodical: Applied Mechanics and Materials (Volume 775)
• Pages: 347-351
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.775.347
• Online since: July 2015
• Authors: Javad Rezapour*, Behzad Bahrami Joo, Ali Jamali, Nader Nariman-Zadeh
• Keywords: Genetic Algorithm, Non-Linear Control, Pareto Optimization, Rollover, Vehicle Dynamic Model

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