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Robust Control for a Biaxial Servo with Time Delay System Based on Neural Network

机译:基于神经网络的时间延迟系统对双轴伺服的鲁棒控制

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A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new neural network based cross-coupled control and neural network techniques are used together to cancel out the skew error. In the proposed control scheme, the conventional fixed gain PID cross-coupled controller (PIDCCC) is replaced with the neural network cross-coupled controller (NNCCC) to maintain synchronization motion of biaxial servo system. In addition, neural network PID (NNPID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with a neural network controller was augmented to set the time delay element be effectively moved outside the closed loop such that the stability of the robust controlled system is enhanced. This scheme provides strong robustness with respect to uncertain dynamics and nonlinearities. The simulation results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.
机译:本文提出了一种用于同步双轴伺服系统运动的鲁棒控制方法。基于新的基于神经网络的交叉耦合控制和神经网络技术一起使用来抵消偏斜错误。在所提出的控制方案中,传统的固定增益PID交叉耦合控制器(PIDCCC)被神经网络交叉耦合控制器(NNCCC)替换为维持双轴伺服系统的同步运动。此外,神经网络PID(NNPID)位置和速度控制器提供必要的控制动作,以在遵循可变命令轨迹时维持同步。增强具有神经网络控制器的延迟时间补偿器(DTC)以设定在闭环外部有效地移动的时间延迟元件,使得增强了鲁棒控制系统的稳定性。该方案对不确定的动态和非线性提供了强大的鲁棒性。仿真结果表明,所提出的控制结构适应广泛的操作条件,并在参数变化和负载变化下提供有前途的结果。

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