采用遥操作模糊神经网络控制系统的跟踪轮移动机器人的稳定性

C. S. Sumathi, R. Ravi Kumar, V. Anandhi
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引用次数: 0

摘要

本研究讨论了采用远程操作系统和路径跟踪方法的跟踪轮移动机器人的稳定性。路径由作为主控机器人的主机进行跟踪。机器人的响应被摄像头捕捉。当从属机器人接近目标位置时,摄像头会捕捉响应机器人的位置和移动轨迹。主机接收到所有图像后,即可恢复移动机器人的偏差。从属机器人可以根据主机器人的决定,使用远程操作来跟踪传感器。模糊神经网络(FNN)控制结构中的 Lyapunov 函数确保了系统的稳定性和令人满意的性能。它支持移动机器人遵守参考轨迹而不偏离轨迹的能力。最后,模拟结果表明,我们的控制器能够跟踪不同的环境条件并保持稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stability of tracking wheel mobile robot with teleoperation fuzzy neural network control system
The stability of the Tracking Wheel Mobile Robot with Teleoperation System and Path Following Method is discussed in this study. The path is to be tracked by the host computer which is the master robot. The response from the robot is captured on camera. As the slave robot approaches the target position, the camera captures the response robot’s position and as well as moving trajectory. The host computer receives all of the images, enabling mobile robot deviation recoveries. The slave robot can use teleoperation to follow the sensor based on the decisions made by the master robot. The Lyapunov function in the Fuzzy Neural Network (FNN) control structure assures the system’s stability and satisfactory performance. It supports a mobile robot’s ability to adhere to a reference trajectory without deviating from it. Finally, the outcome of the simulation demonstrates that our controller is capable of tracking different environmental conditions and maintaining stability.
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