RBF neural network adaptive dynamic surface control method based on flexible joint of robot arm

Abstract

The invention relates to an RBF neural network adaptive dynamic surface control method based on a flexible joint of a robot arm, belonging to the technical field of artificial intelligence and intelligent control. The invention aims at modeling the flexible joint existing in the robot arm, and designs a controller by combining the RBF neural network and the dynamic surface technology with an adaptive control method. The RBF neural network is used to compensate the uncertainties of system parameters, an adaptive law is used to adjust the weights of the neural network to improve the approximation ability of the RBF neural network to nonlinear functions and eliminate the need for precise dynamic model of the robot arm. A position tracking control algorithm suitable for the light robot arm with flexible joints is studied. At last, the design controller is verified by a simulation example, and the invention can ensure that the joint can effectively track a given signal under the condition that the output torque of the robot arm is limited, the tracking error is unconstrained in a certain range, and all signals are semi-globally bound.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and control, and in particular relates to an RBF neural network self-adaptive dynamic surface control method of a flexible joint of a mechanical arm. Background technique [0002] Since the 1960s, robots have been widely used in industry, such as machining, arc welding, spot welding, spraying, assembly, testing, aerospace, space exploration, etc. For a long time, industrial robots have occupied an important position in industrial automation production lines. However, with the expansion of the application range of robots, people have found that the fixed and repetitive operations of industrial robots cannot meet the needs of more and more flexible tasks, such as tasks that change with the location and require different tasks. Therefore, engineering designs lightweight robotic arms that meet such special requirements. Light-duty robotic arms are mostly used in previously unknown working envi...

AI Technical Summary

Problems solved by technology

For flexible articulated robots, in addition to the uncertainty in the system and the research on output feedback control, due to the limitation of the output power of the joint motor itself, there is a saturation limit for the output torque of the robot joint driver. Although many studies have been carried out, But there is no better solution

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