A control method for model prediction and inversion for manipulating a manipulator

Abstract

The invention discloses a model prediction and inversion control method of a manipulator. According to the state information measured in the current k cycle, the state information of the platform and the manipulator in the k+nth control cycle is predicted, and based on the generalized inverse matrix theory , and reversely deduce the control input of the k~k+n-1 period platform and the control input of the manipulator. Based on the deviation information of the current and historical states, the compensation control input of the platform and the manipulator in the current k-th control cycle is reversely derived to weaken the state deviation caused by factors such as external disturbance and parameter uncertainty. The sum of the control input of the kth control cycle obtained from the predicted state deviation and the compensation control input obtained from the current and historical state deviations is used as the control input of the kth control cycle to be applied to the platform and the manipulator. In this way, high-precision platform attitude and trajectory tracking control of manipulator joints can be realized, and it has strong anti-interference ability to parameters and external disturbances.

Description

technical field [0001] The invention relates to the field of robots, in particular to a model prediction and inversion control method of a mechanical arm. Background technique [0002] The manipulator has the characteristics of time-varying, nonlinear and strong coupling, and it has broad application prospects in various fields such as industry, commerce, military, aerospace and so on. For example, robots are used in industrial production lines for handling, spraying, and assembly; in the military field, they are used to replace human soldiers to complete various combat tasks such as reconnaissance, use of weapon vehicles, and target removal; in the medical field, they are used for automatic or remote control to complete operations; aerospace, etc. The field is used for a variety of important tasks such as assisting astronaut activities, assisting spacecraft docking, transporting materials, completing assembly, maintenance, and fueling. Many application fields put forward h...

AI Technical Summary

Problems solved by technology

At present, PID control, fuzzy control, sliding mode variable structure control, adaptive control, neural network control and other methods of manipulators have poor control accuracy / stability, and are not robust to disturbance loads and manipulator body parameters. , The human subjective factors of the controller design are greatly affected, usually designed from the perspective of stability, it is difficult to ensure good dynamic performance and steady-state performance at the same time

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