Self-adaptive teleoperation control method for neural network based on radial basis function

Abstract

The invention discloses a self-adaptive teleoperation control method for a neural network based on a radial basis function. The self-adaptive teleoperation control method comprises three steps of respectively establishing dynamics models for a master manipulator end and a slave manipulator end in a teleoperation system, designing a slave manipulator end controller, and finally designing a master manipulator end controller. According to the self-adaptive teleoperation control method, the stability and relatively good operating performance in the teleoperation process can be guaranteed. When the slave manipulator end for teleoperation, namely a slave end manipulator grabs a target object, uncertainty of kinematics and dynamics parameters of the system occurs. The controller is designed for the slave manipulator end by use of a self-adaptive controller for an RBF neural network, so that the advantages of a self-adaptive control method can be played, the self-learning ability for and the adaptivity to the uncertainty in the teleoperation system are realized, and further the parameter uncertainty and the influence of unknown interference on the teleoperation system are overcome.

Description

【Technical field】 [0001] The invention belongs to the technical field of remote operation, relates to bilateral control and self-adaptive control technology, and can be used in a control method for a single hand controller device to operate a single manipulator. 【Background technique】 [0002] Teleoperation technology is a real-time control technology that can project human intelligence to a remote environment. Due to the limitation of the current intelligent level of robots, in some specific occasions and tasks, robots cannot be completely relied on to complete operational tasks. Through the teleoperation technology, the operator can control the remote robot equipment in real time across the limitation of space distance, and complete specific operation tasks accurately and effectively. In the medical field, remote operation technology can enable medical personnel to overcome distance limitations, eliminate intractable diseases and even perform surgery for patients; in resc...

AI Technical Summary

Problems solved by technology

In the actual teleoperation process, when the slave-end manipulator grabs the target, or when the slave-end environment produces some unknown interference to the slave-end manipulator, the kinematics and dynamics parameters of the teleoperation system will change, and the previous control The system cannot deal with the impact of these kinematic and dynamic parameter changes well, which may lead to instability or even teleoperation failure during the teleoperation process.

Even if these kinematics and dynamics parameters can be accurately obtained through calibration and parameter identification techniques, it is not advisable and inflexible to perform calibration and parameter identification on each target when the robot grabs it.

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