Abstract
Through an analysis of the kinematics and dynamics relations between the target positioning of manipulator joint angles of an apple-picking robot, the sliding-mode control (SMC) method is introduced into robot servo control according to the characteristics of servo control. However, the biggest problem of the sliding-mode variable structure control is chattering, and the speed, inertia, acceleration, switching surface, and other factors are also considered when approaching the sliding die surface. Meanwhile, neural network has the characteristics of approaching non-linear function and not depending on the mechanism model of the system. Therefore, the fuzzy neural network control algorithm can effectively solve the chattering problem caused by the variable structure of the sliding mode and improve the dynamic and static performances of the control system. The comparison experiment is carried out through the application of the PID algorithm, the sliding mode control algorithm, and the improved fuzzy neural network sliding mode control algorithm on the picking robot system in the laboratory environment. The result verified that the intelligent algorithm can reduce the complexity of parameter adjustments and improve the control accuracy to a certain extent.
Highlights
With the development of science and technology, robot technology has acquired unprecedented achievements
According to the characteristics of apple-picking robot motion control, the image-based robot visual servo control method is combined with the improved fuzzy neural network sliding mode control algorithm to make use of the non-linear and non-system-dependent mechanism model of the fuzzy neural network
The research aim of this paper is mainly to verify the visual servo control of the sliding-mode control algorithm based on the improved fuzzy neural network through the apple-picking robot
Summary
With the development of science and technology, robot technology has acquired unprecedented achievements. In the field of robotic citrus picking, there is a non-linear robust image visual servo controller that can adjust the end effector to the fruit position under the condition of unknown fruit movement, but the speed of the picking process is slow, and is not conducive to agricultural application [14]. A joint visual servo control algorithm based on an improved sliding mode and kinematics and dynamics equation is presented that appears to have good robustness in a non-linear system. According to the characteristics of apple-picking robot motion control, the image-based robot visual servo control method is combined with the improved fuzzy neural network sliding mode control algorithm to make use of the non-linear and non-system-dependent mechanism model of the fuzzy neural network. The research aim of this paper is mainly to verify the visual servo control of the sliding-mode control algorithm based on the improved fuzzy neural network through the apple-picking robot. It is concluded that the improved fuzzy neural network sliding mode control algorithm can improve the efficiency of the robot arm servo control and has higher stability
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