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Control of time varying nonlinear system of supporting robot based on neural network

机译:基于神经网络的支撑机器人的时变非线性系统的控制

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This paper takes mining hydraulic supporting robot as the research object. On the basis of analyzing the dynamic model of the supporting robot and transfer functions of the hydraulic system, system construction and simulation are realized in Simulink. Due to the existence of time-varying parameters in the system, common negative feedback controls are not effective and stable. Therefore, a neural network adaptive PID controller is proposed in this paper, and results are analyzed and compared with traditional PID control. Results show that the neural network adaptive PID controller has fast response speed and very small overshoot. The remarkable feature is that the system shows an excellent adaptive ability to quickly return to the control position after interference impacts, which fully demonstrates the effectiveness of the neural network adaptive PID controller for hydraulic supporting robot time-varying system.
机译:本文采用矿井液压支撑机器人作为研究对象。在分析液压系统支持机器人的动态模型和液压系统的传递函数的基础上,在Simulink中实现了系统构造和仿真。由于系统中的时变参数存在,常见的负反馈控制无效且稳定。因此,在本文中提出了一种神经网络自适应PID控制器,并与传统的PID控制进行了分析并将结果进行了分析。结果表明,神经网络自适应PID控制器具有快速响应速度和非常小的过冲。显着的特征是该系统显示出在干扰冲击后快速返回到控制位置的优异自适应能力,这完全展示了用于液压支撑机器人时变系统的神经网络自适应PID控制器的有效性。

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