Large condenser underwater operation environment two-joint robot control method

Abstract

The utility model discloses a control method for controlling a two-joint robot of an underwater-operation condenser. Processes are as following: {1} A controller structure of a fuzzy Kovski neural network is built up and each sub-network represents a serve controller of a joint; {2} Every parameter of the control system and weighted value of network is initialized; an error of an angular displacement of two joints and rate of error is obtained based on the current angular displacement of two joints and expected motion angle displacement; {3}The error and the rate of error are used as the input of the fuzzy Kovski neural network controller and obtain moment exerted on motor points of two joints by fuzzy Kovski neural network controller. Tthe moment is used to control an electric motor, making the joints reach expected elements of a fix. The invention can overcome the difficulty in self-modeling of the robots and uncertainty of environmental disturbance. The utility model can not only sum up experience in controlling of human experts but also have self-study function of neural network controller, thereby reaching a higher controlling degree of accuracy.

Description

technical field [0001] The invention mainly relates to the field of control of a two-joint robot, in particular to a control method of a two-joint robot in a large condenser underwater working environment. Background technique [0002] The real development of robots began in the 1940s, and the first industrial robot came out in 1959 at the Unimation Corporation of the United States, which marked the beginning of robots entering industrial applications. So far, about 80% of the robots used in practice are located in industrial sites and belong to industrial robots. This type of robot has the characteristics of simple structure, known working environment, and pre-set robot work. Therefore, it also determines that the control of the robot belongs to the demonstration In the teaching and reproduction model, the working path and motion parameters of the robot need to be taught by the operator manually or through online programming. Basically, the operation demonstrated by the ope...

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Problems solved by technology

Since the robot works in an underwater environment, there are uncertainties in signal measurement and system modeling, coupled with complex environmental changes and external uncertain disturbances caused by water flow (speed, intensity), water temperature, water pressure, etc., Therefore, it is impossible to obtain the precise and complete motion model of the robot, so conventional control methods and modern control methods cannot or are difficult to guarantee the control accuracy, and there are problems such as being too complicated or unable to guarantee the real-time performance of the control.

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