【摘 要】
:
为提高矿用车辆在转向工况下的动态性能,建立了包含空气弹簧非线性模型的转向工况下矿用车辆空气悬架阻尼力控制模型,应用自适应神经网络控制方法,设计了基于可调阻尼减振器
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为提高矿用车辆在转向工况下的动态性能,建立了包含空气弹簧非线性模型的转向工况下矿用车辆空气悬架阻尼力控制模型,应用自适应神经网络控制方法,设计了基于可调阻尼减振器的空气悬架阻尼力神经网络控制器,对控制器的控制性能进行了仿真分析,仿真结果表明,设计的控制器能够有效提升矿用车辆在转向工况下的操稳性和平顺性。
In order to improve the dynamic performance of mining vehicles under steering conditions, a control model of damping force of mine air suspension is set up under steering conditions including air spring nonlinear model. Based on the adaptive neural network control method, The air suspension damping force neural network controller with damping damper is used to simulate the control performance of the controller. The simulation results show that the designed controller can effectively improve the handling stability of the mining vehicle under steering conditions And ride.
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