| 基于神经网络非线性模型的线控转向系统控制 |
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| 引用本文： | 于蕾艳,伊剑波,鲍长勇.基于神经网络非线性模型的线控转向系统控制[J].拖拉机,2014(2):37-40. |
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| 作者姓名： | 于蕾艳 伊剑波 鲍长勇 |
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| 作者单位： | 中国石油大学（华东）机电学院,山东青岛266580 |
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| 基金项目： | 国家自然科学基金项目（51005248,51005115）,中央高校基本科研业务费专项资金资助（11CX04039A） |
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| 摘 要： | 进行汽车线控转向系统动力学分析及控制算法研究，需考虑动力学模型的非线性。首先建立基于魔术公式轮胎模型的非线性二自由度整车模型，然后基于神经网络方法训练逼近映射汽车模型输入与输出的关系，最后采用模糊控制方法由车速、转向盘转角等得到转向传动比控制算法。结果表明，基于神经网络的非线性整车模型与样本数据较好吻合，满足研究需要。转向传动比模糊控制算法考虑了转向轻便性和稳定性，提高了汽车操纵稳定性。
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| 关 键 词： | 线控转向系统 神经网络 非线性二自由度整车模型 转向传动比 模糊控制 |
Control of Steer By Wire System Based on Artificial Neural Network Nonlinear Model |
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| Authors: | YU Lei-yan YI Jian-bo BAO Chang-yong |
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| Institution: | (Department of Mechanical and Electronic Engineering, China University of Petroleum, Qingdao 266580, China) |
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| Abstract: | Nonlinear characteristics of automobile steer by wire system dynamics models need to be considered to perform more accurate dynamics analysis and control algorithm research. Firstly, tire model based on Magic Formula was adopted, and nonlinear two degree of freedom overall vehicle dynamics model was built using MATLAB software. Then, the model was trained using artificial neural network method to reflect the relations between inputs including velocity and steering wheel angles and outputs including vehicle slip angle and yaw rate. Finally, steering ratio algorithm determined by velocities and steering wheel angles using fuzzy control method was researched. The results show that the nonlinear vehicle model based on artificial neural network fits the data so well that it can satisfy the needs of dynamics analysis and control algorithm. The built steering ratio algorithm considers both the steering agility and steering stability, so it can improve handling and stability of vehicles. |
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| Keywords: | Steer by wire system Artificial neural network Nonlinear two degree of freedom overall vehicle dynamics model Steering ratio Fuzzy control |
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