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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时变非线性系统控制

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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:本文以采矿液压支撑机器人为研究对象。在分析支撑机器人的动力学模型和液压系统传递函数的基础上,在Simulink中实现了系统的构建和仿真。由于系统中存在时变参数,因此常见的负反馈控制无效且不稳定。因此,本文提出了一种神经网络自适应PID控制器,并与传统PID控制进行了分析和比较。结果表明,神经网络自适应PID控制器响应速度快,超调量很小。该系统的显着特点是具有出色的自适应能力,在受到干扰影响后能够快速返回控制位置,这充分证明了神经网络自适应PID控制器在液压支持机器人时变系统中的有效性。

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