基于CMAC神经网络的Lugre摩擦模型双伺服电机同步

2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET) Pub Date : 2021-09-13 DOI:10.1109/IICAIET51634.2021.9573974

Suprapto, Taufik, A. Nasuha, E. Riyanto

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引用次数: 1

摘要

由于双伺服电机控制在电动汽车、机器人、电子生产机械等工程领域的广泛应用，双伺服电机的同步控制已成为一个重要的问题。本文研究了小脑模型关节控制器(CMAC)和神经网络控制器(NN)在动态LuGre摩擦模型下同步两台伺服电机。CMAC是一种以联想记忆为代表的神经网络方法，具有更强大的特性。本研究采用交叉耦合控制结构对两台伺服电机进行同步。为了研究其性能，应用MATLAB Simulink对双伺服电机的控制设计进行了仿真。仿真结果表明，CMAC控制器具有较好的输出轨迹，能够很好地控制两个不同参数的LuGre摩擦模型伺服电机。

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Synchronization of Dual Servo Motor Using CMAC Neural Network-based Lugre Friction Model

Synchronization of dual servo motor control has become an important issue due to many applications in engineering fields, such as electric vehicle, robotics, electronics production machines, and others. This paper studies cerebellar model articulation controller (CMAC) neural network (NN) controller to synchronize two servo motors with dynamic LuGre friction model. CMAC is kind of NN method represented by associative memory with more powerful properties. Cross-coupling control structure is employed to synchronize two servo motors in this study. To investigates the performance, MATLAB Simulink is applied to simulate the control design of dual servo motor. The simulation results exhibit that CMAC controller has better output trajectory and works well for two servo motors with different parameters of LuGre friction model.

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来源期刊

2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

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