High-precision control device and method used for industrial robot

Abstract

The invention provides a high-precision control device and method used for an industrial robot. The method comprises the steps that a six-dimensional force-torque sensor mounted between a base and a fixed face of the industrial robot is utilized for measuring the bearing reaction and torque transmitted by connecting rods to a pedestal in the operation process of the industrial robot, and joint motion power is observed; linear kinetic model parameters obtained through observation are estimated and corrected online in real time, and linear model estimation joint motion power phi<d,model> is obtained; joint friction force phi<friction> is estimated online according to joint drive torque phi<motor> and the linear model estimation joint motion power phi<d,model>; and according to the parametersobtained through joint motion power observation and online estimation of the joint friction force phi<friction>, a model based robot control algorithm is adopted for achieving high-precision controlof the industrial robot. According to the method, decoupled identification of friction force parameters and robot mass distribution characteristic parameters is achieved, a quite precise robot kineticmodel is obtained online, and the method can be applied to the scene with the high requirement for control precision of the industrial robot.

Description

technical field [0001] The invention relates to the technical field of industrial robots, in particular to a high-precision control device and method for industrial robots. Background technique [0002] Model-based control is an important technical approach to achieve high-precision control of industrial robots, but the premise of this method is to obtain a sufficiently accurate robot dynamic model, including the mass distribution characteristic parameters of the robot structure, friction parameters of the transmission system, etc. At present, there are two main ways to obtain the dynamic parameters of industrial robots: the nominal model parameters given by design and empirical parameters and the robot dynamic parameters identified by the robot body parameter identification technology. The problem with the first method is that due to the processing Due to the existence of production deviation, the actual kinetic parameters are quite different from the nominal parameters, an...

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Problems solved by technology

At present, there are two main ways to obtain the dynamic parameters of industrial robots: the nominal model parameters given by design and empirical parameters, and the robot dynamic parameters identified by the robot body parameter identification technology. The problem with the first method is that due to the processing Due to the existence of production deviation, there is a big difference between the actual kinetic parameters and the nominal parameters, and the application of nominal parameters cannot accurately describe the actual kinetic characteristics

The second method can obtain dynamic model parameters with a certain accuracy. It is widely used at present, but there are certain problems. For example, the parameter identification is carried out in the same group of motions, and the inertial force, Coriolis force, gravity and friction force in the driving torque are different. The specific gravity is determined by the characteristics of the identification motion. In order to fully identify the components, the identification motion needs to be carefully designed. In addition, the friction force is affected by the actual working conditions. The working conditions are not exactly the same, so the dynamic model parameters obtained by the above two methods are difficult to meet the requirements of model-based control of high-precision industrial robots

[0003] In some model-based industrial robot control schemes, in order to eliminate the uncertainty of the dynamic model parameters, the adaptive control method is used to modify the model parameters online, which has a certain effect, but the problem is that the friction and motion force parameters in the joint torque Estimated during the measurement, due to the influence of Coulomb friction nonlinearity, the convergence accuracy of the online identification of dynamic parameters is limited

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