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TWO-PORT NETWORK BASED BILATERAL CONTROL OF A STEER-BY-WIRE SYSTEM
X. WU,C. YE,M. XU,A. KAKOGAWA 한국자동차공학회 2016 International journal of automotive technology Vol.17 No.6
Steer-by-wire (SBW) system which is characterized by variable steering feel, better active safety, unmanned drive, has been widely studied to realize a distinctive driving experience. Control strategy acts as a key part of SBW system to achieve the goals. In this paper, a control strategy by bilateral control structure for steer-by-wire system is proposed. To make SBW system has the same function of conventional steering systems, the controller is designed to realize desired tracking control and realistic road feel feedback. The control of position and torque for each actuator is taken as two ports for the control network. Based on different control loop, two kinds of bilateral control is investigated respectively. The hardwarein- the-loop experiment platform of SBW is developed by the reconfiguration of electric power steering system. The test results are compared to show the performance of different control loops.
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ADAPTIVE FEEDFORWARD CONTROL OF A STEER-BY-WIRE SYSTEM BY ONLINE PARAMETER ESTIMATOR
Xiaodong Wu,Mingming Zhang,Min Xu,Yo Kakogawa 한국자동차공학회 2018 International journal of automotive technology Vol.19 No.1
The tracking control of the steer-by-wire (SBW) system to achevie desired steering motion is the core issue for the design of algorithm. Most of model-based tracking control assumed the constant parameters without the consideration of dynamic characteristics. The external disturbances and model nonlinearities can bring uncertainties of the system parameters. To reduce the influence of parameter uncertainties, an online estimator by output error identification method is proposed to estimate the dynamic parameters of a SBW system. Meanwhile, the parameter gradient projection method is applied to eliminate the parameter drift, while a full order state observer is developed to weaken the effects of noise disturbance during the parameter identification. Since the sensitivity of parameter uncertainties for the feedforward control, the online estimator is incorporated into the control model and improve the controlled robustness. The proposed adaptive feedforward controller is conducted by the real-time experiments to show the tracking performance.
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