Industrial robots are currently the most widely used and also the most mature and sophisticated type of robot on the market. Industrial robots employ various control methods. What are the control methods for industrial robots?
1. Point Control Mode (PTP)
Point position control is widely used in mechatronics and robotics industries. Typical applications include CNC machine tool tracking of part contours, fingertip trajectory control of industrial robots, and path tracking systems for walking robots in the machinery manufacturing industry.
During the control process, industrial robots are required to move quickly and accurately between adjacent points, and there are no restrictions on the trajectory for reaching the target point.
Positioning accuracy and movement time are the two main technical indicators of this control mode. This control method is easy to implement with low positioning accuracy and is typically used for loading, unloading, and handling spot welding, where the inserted components on the circuit board should maintain the end effector in the accurate position of the target point. This method is relatively simple, but achieving a positioning accuracy of 2-3 μm is difficult.
Point control systems are essentially position servo systems. Their basic structure and composition are basically the same, but the control complexity varies depending on the focus; based on feedback, they can be divided into closed-loop systems, semi-closed-loop systems, and open-loop systems.
2. Continuous Trajectory Control Mode (CP)
Under the control of the point position, the start and end speeds of PTP are 0, and various speed planning methods can be used during this period.
CP control is the continuous control of the position of the end effector of an industrial robot in the workspace. The velocity at the intermediate point is not zero. It moves continuously. The velocity at each point is obtained by looking forward. Generally, continuous trajectory control mainly uses the velocity look-forward method: forward speed limit, angular velocity limit, tracking speed limit, maximum speed limit, and contour error speed limit.
This control method requires it to move strictly according to a predetermined trajectory and speed within a certain precision range, with controllable speed, smooth trajectory, stable motion, and successful completion of the task.
The joints of industrial robots are continuous, and through synchronized movement, the end effector can form a continuous trajectory. The main technical indicators of this control mode are the tracking accuracy and stability of the end effector position, typically used in arc welding and painting. This control method is also used for robot deburring and inspection.
3. Force (torque) control methods
As the application boundaries of robots continue to expand, vision-based capabilities alone are no longer sufficient to meet the demands of complex real-world applications. In such cases, it is necessary to introduce force/torque to control the output, or to introduce force or torque as closed-loop feedback.
When grasping and placing objects, assembly is underway. Besides precise positioning, appropriate force or torque is required, necessitating the use of a (torque) servo. The control principle is essentially the same as that of a position servo control system, but the input and feedback are not position signals; instead, they are force (torque) signals. Therefore, a powerful (torque) sensor must be used in the system. Sometimes sensing functions such as proximity, adaptive control, and sliding are also employed.
Since the contact between the robotic arm and the working surface is usually an unknown and complex surface, the force/torque sensing should also have multidimensional capabilities.
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 and pneumatic components, limit switches, and other electromechanical components acquire knowledge of the surrounding environment and make corresponding decisions based on their internal knowledge base.
The development of intelligent control technology relies on the rapid advancements in artificial intelligence expert systems, such as artificial neural networks, genetic algorithms, and so on. In recent years, intelligent control technology has made significant progress. Fuzzy control theory, artificial neural network theory, and their integration have greatly improved the speed and accuracy of robots. These technologies are primarily used in the tracking control of multi-joint robots, lunar robot control, weeding robot control, and cooking robot control.
Robot intelligent control can be categorized into: fuzzy control, adaptive control, optimal control, neural network control, fuzzy neural network control, and expert control.
What are the control methods for industrial robots? Most robots are still at a relatively basic stage of spatial positioning and control, lacking significant intelligence and having a long way to go before achieving true intelligence. Therefore, Chinese robot experts, based on their application environments, divide robots into two main categories: industrial robots and intelligent robots.
