What are the common control methods of industrial robots?
Robots, in most cases, are still at the lower level of the space positioning control stage. There is not much intelligence, and there is still a long way to go before intelligence. Therefore, our robot experts divide robots into two categories, namely industrial robots and intelligent robots, based on the application environment.
At present, the most widely used robot in the market is industrial robot, which is also the most mature and perfect robot. Industrial robots have many control methods. What are the common control methods for industrial robots?
1. Point control mode (PTP)
Point position control is widely used in electromechanical integration and robot industry. The typical applications of NC machine tool tracking part contour, industrial robot fingertip trajectory control and walking robot path tracking system in mechanical manufacturing industry.
In the control process, industrial robots are required to be able to move quickly and accurately between adjacent points, and there is no regulation on the moving track to reach the target point.
Positioning accuracy and moving time are two main technical indicators of the control mode. This control method is easy to achieve low positioning accuracy and is usually used for loading, unloading and handling spot welding. The plug-in components on the circuit board should maintain the accurate position of the terminal actuator at the target point. This method is relatively simple, but it is difficult to achieve the positioning accuracy of 2~3 um.
The point control system is actually a position servo system. Its basic structure and composition are basically the same, but the control complexity is different due to different emphasis; According to feedback, it can be divided into closed loop system, semi closed loop system and open loop system.
2. Continuous trajectory control mode (CP)
Under the control of the point position, the starting and ending speeds of PTP are 0, during which various speed planning methods can be used.
CP control is to continuously control the position of industrial robot terminal actuator in the workspace. The velocity at the midpoint is not zero. It keeps moving. The speed of each point is obtained by looking forward. Generally speaking, continuous trajectory control mainly adopts speed look ahead method: forward speed limit, corner speed limit, tracking speed limit, maximum speed limit and contour error speed limit.
The joints of industrial robots are continuous and continuous. Through synchronous motion, the terminal actuator can form a continuous trajectory. The main technical index of this control mode is the tracking accuracy and stability of the terminal actuator position of the industrial robot, usually arc welding and painting. This control method is used for robot deburring and inspection.
3. Force (torque) control method
With the continuous expansion of robot application boundaries, visual empowerment alone can no longer meet the needs of complex practical applications. At this time, force/torque must be introduced to control the output, or force or torque must be introduced as closed-loop feedback.
When grabbing and placing objects, the assembly is in progress. In addition to precise positioning, it is necessary to use appropriate force or torque, and then (torque) servo must be used. The control principle is basically the same as the position servo control principle, but the input and feedback are not position signals, but force (torque) signals. Therefore, powerful (torque) sensors must be used in the system. Sensing functions such as proximity, adaptive control, and sliding are sometimes used.
4. Intelligent control mode
Robot intelligent control is a control mode that uses sensors (such as cameras) to control intelligent information processing, intelligent information feedback and intelligent control decisions. Image sensors, ultrasonic transmitters, lasers, conductive rubber, piezoelectric components and pneumatic components, travel switches and other electromechanical components) acquire the knowledge of the surrounding environment and make corresponding decisions according to their own internal knowledge base.
The development of intelligent control technology depends on the rapid development of artificial intelligence expert systems such as artificial neural networks, genetic algorithms and genetic algorithms. In recent years, intelligent control technology has made significant progress. Fuzzy control theory, artificial neural network theory and their integration greatly improve the speed and accuracy of the robot. It is mainly used for multi joint robot tracking control, lunar robot control, weeding robot control, cooking robot control, etc.
Robot intelligent control can be divided into fuzzy control, adaptive control, optimal control, neural network control, fuzzy neural network control and expert control.