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Adaptive fuzzy sliding mode control for electric power steering system

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Abstract

The Electric power steering (EPS) system, a typical non-linear system, is easy to be influenced by parameters perturbation and disturbance of the road. Traditional linear control method based on a simplified linear model such as PID control cannot reach good dynamic performance. To reduce the influence of parameters perturbation and disturbance of the road and enhance the robustness of the system, an Adaptive fuzzy sliding mode control (AFSMC) method is proposed in this paper. First, fuzzy sliding mode control is employed to enhance the dynamic performance of the system. Then, to improve the precision of the controller, genetic algorithm is used to optimize the control rules which are essential to fuzzy control. The experimental results on non-linear EPS model demonstrate that AFSMC is more stable than Sliding mode control (SMC) method and more efficient to the non-linear system than SFPID control method. They can also prove that AFSMC can provide a stable driving in the presence of parameters perturbation and disturbance of the road.

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Correspondence to Changhao Piao.

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Recommended by Associate Editor Hyoun Jin Kim

Sheng Lu received his B.S. from Xi`an Jiaotong University in 2004, China. In 2009, he received his M.S. and D.S. from Inha University, S. Korea. Now he is a Professor of Chongqing University of Posts and Telecommunications, China. His interests include automobile electronics, micro-nano mechanics, and intelligent materials.

Changhao Piao received his B.E. from Xi'an Jiaotong University in 2001, China. Then, he received his M.E. and D.E. from Inha University, S. Korea in 2007. Now he is a Professor of Chongqing University of Posts and Telecommunications, China. His research interests include automobile electronics, energy electronics and EHW. He has published more than 80 publications including papers, books and patents.

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Lu, S., Lian, M., Liu, M. et al. Adaptive fuzzy sliding mode control for electric power steering system. J Mech Sci Technol 31, 2643–2650 (2017). https://doi.org/10.1007/s12206-017-0507-4

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  • DOI: https://doi.org/10.1007/s12206-017-0507-4

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