Design method and system of closed-loop fractional-order pdɑ-type iterative learning robot controller

Abstract

The invention discloses a design method and a design system of a closed-loop fractional-order PD<alpha> type iterative learning robot controller. The design method comprises the steps of: selecting a movement mechanism of a robot as an analysis object, constructing a kinetic model of the selected movement mechanism and a closed-loop fractional-order PD<alpha> type iterative learning control law in the robot controller; presetting an expected movement trajectory of the movement mechanism of the robot, initializing an input quantity and parameters of the closed-loop fractional-order PD<alpha> type iterative learning control law and applying the input quantity and the parameters to the movement mechanism of the robot, and acquiring an actual movement trajectory of the robot; judging whether an error between the acquired actual movement trajectory and the expected movement trajectory is zero, if so, indicating that the acquired actual movement trajectory coincides with the expected movement trajectory and current parameters of an iterative learning law are unchanged, and acquiring the optimal parameters of the robot controller; otherwise, jumping to a next step of adjusting the parameters of the iterative learning law until the optimal parameters of the robot controller are obtained.

Description

technical field [0001] The invention belongs to the field of robot control, in particular to a closed-loop fractional-order PD α A design method and system for a type iterative learning robot controller. Background technique [0002] Robotics is currently a research hotspot in academia and industry around the world. With the development of science and technology, robots have been widely used in various fields such as aerospace, medical and military, and even daily life, entertainment and education. Robots are not only the key supporting equipment for advanced manufacturing, but also an important entry point for improving human life style. With the increasing maturity of theory and technology, people have put forward more and more requirements for robots. [0003] The robot system is a typical highly nonlinear and strongly coupled dynamical system, and its high-precision control has always been a research hotspot in the field of industrial automation. For example: the cur...

AI Technical Summary

Problems solved by technology

[0004] The existing learning control method can realize the complete tracking of the robot to the expected trajectory. However, when the system is affected by environmental factors or its own state, the adaptability of the existing control method is not strong, and it needs to be relearned to achieve a better tracking effect.

On the other hand, the existing learning control methods are all integer-order algorithms, and the controller has fewer adjustable parameters, which also makes the controller less stable and adaptable.

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