Research on Multidisciplinary Modeling and Robust Control for Electric Power Steering System

2011 ◽  
Vol 179-180 ◽  
pp. 179-185 ◽  
Author(s):  
Guo Jin Chen ◽  
Hui Peng Chen ◽  
Li Ping Chen
Keyword(s):  
Robust Control ◽  
Control Algorithm ◽  
Control Structure ◽  
Steering System ◽  
Electric Power Steering ◽  
Power Steering System ◽  
Loop Control ◽  
Power Steering ◽  
Multidisciplinary Modeling ◽  
Electric Power Steering System

The first of all, the multidisciplinary modeling and analyzing for the electric power steering system (EPS) is made. The design method based on the model is proposed and the EPS control system is analyzed. On the basis of deeply observing and studying S/T singular value curves, a robust control algorithm of back-calculation is put forward. After analyzing the deficiency in the single-loop control structure of the EPS, the dual-loop control structure of the EPS is developed. The inner loop controller is designed using the single neuron PID algorithm, and the new robust control algorithm is proposed to design the outer loop controller. The simulation results in the frequency-domain S/T curves of the EPS system and the hand force step input of the steering wheel show that the designed controller is simple and effective, and has good robust stability and robust performance.

Research on Assistance Control Algorithm for Electric Power Steering System Based on Robust Control Theory

2013 ◽  
Vol 655-657 ◽  
pp. 1397-1402
Author(s):  
Chao Ying Liu ◽  
Wen Jiang Wu ◽  
Zhan Zhong Wang ◽  
Zhan Feng Gao
Keyword(s):  
Robust Control ◽  
Electric Power ◽  
Control Algorithm ◽  
Steering System ◽  
Robust Controller ◽  
Electric Power Steering ◽  
Power Steering System ◽  
The Road ◽  
Power Steering ◽  
Electric Power Steering System

Assistance control is an important control model of electric power steering system. When designing assistance control algorithm, we should not only consider the handiness and stability of steering, but also think of the assistance stability and disturbance resistance from the road surface. In order to improve the overall performance of electric power steering, robust control theory is applied to develop the assistance control algorithm. Based on the above, a robust controller was designed. The influences of the assistance torque deviation and the road surface disturbance on steering were selected as the controlled output. Then the designed controller was tested on electric power steering test bed. The test results show that the robust controller is of better assistant performance than traditional PID controller.

Robust control for fuzzy electric power steering system: A two-layer performance approach

2021 ◽  
pp. 107754632110034
Author(s):  
Duo Fu ◽  
Subhash Rakheja ◽  
Wen-Bin Shangguan ◽  
Hui Yin
Keyword(s):  
Robust Control ◽  
Electric Power ◽  
Control Design ◽  
Steering System ◽  
Fast Time ◽  
Electric Power Steering ◽  
Power Steering System ◽  
Power Steering ◽  
Electric Power Steering System ◽  
Mismatched Uncertainty

This study investigates the angle tracking control of the electric power steering system, which is underactuated and with (possibly fast) time-varying uncertainties. We design the control based on constraint-following, that is, formulating the tracking goal as servo constraints. To tackle the uncertainty, especially the mismatched uncertainty, a robust control is proposed with two-layer performance: deterministically guaranteed and fuzzily optimized. Particularly, the control design is implemented in three steps. First, without considering uncertainty, a nominal control is designed. Second, an uncertainty decomposition technique is presented to account for uncertainty, which creatively allocates the mismatched uncertainty for the robust control design that also builds on the nominal system control. The robust scheme is deterministic without using any “if–then” rules and guarantees uniform boundedness and uniform ultimate boundedness for the system, that is, the deterministically guaranteed performance. Third, by using fuzzy set theory to describe uncertainty, a fuzzy-based performance index, including system performance and control cost, is introduced. A control parameter optimal design problem is formulated and analytically solved, that is, the fuzzily optimized performance. The effectiveness of the proposed approach is illustrated by rigorous proof and the simulation results on the electric power steering system.

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