What are the general control methods for flexible robotic arms?

In recent years, with the development of robotics technology, robot structures with high speed, high precision, and high load-to-weight ratio have attracted attention in the industrial and aerospace fields. Due to the increase in the flexibility of joints and connecting rods during movement, the structure deforms, which reduces the accuracy of task execution. Therefore, the flexibility characteristics of the robot manipulator structure must be considered, and the system dynamics characteristics must also be considered to achieve high-precision and effective control of the flexible manipulator.

The flexible manipulator is a very complex dynamic system, and its dynamic equations have the characteristics of nonlinearity, strong coupling, and real variation. The establishment of its model is extremely important for the study of the dynamics of the flexible manipulator. The flexible manipulator is not only a nonlinear system of rigid-flexible coupling, but also a nonlinear system of electromechanical coupling in which the system dynamic characteristics and control characteristics are coupled with each other.

The control of the flexible robotic arm is generally carried out in the following ways:

1. Rigidization. The influence of elastic deformation of the structure on the rigid body motion of the structure is completely ignored. For example, in order to avoid excessive elastic deformation that may damage the stability and end positioning accuracy of the flexible robotic arm, the maximum angular velocity of NASA's remote-controlled space arm is 0.5 deg/s.

2. Feedforward compensation method. The mechanical vibration caused by the flexible deformation of the robot arm is regarded as a deterministic interference to the rigid motion and the feedforward compensation method is used to offset this interference. Bernd Gebler of Germany studied the feedforward control of industrial robots with elastic rods and elastic joints. Zhang Tiemin studied the method of eliminating the dominant poles and system instability of the system by adding zero points, and designed a feedforward controller with time delay. Compared with the PID controller, it can more obviously eliminate the residual vibration of the system.

3. Acceleration feedback control. Khorrami FarShad and Jain Sandeep studied the problem of using end acceleration feedback to control the end trajectory of a flexible manipulator.

4. Passive damping control. In order to reduce the influence of the relative elastic deformation of the flexible body, various energy dissipation or energy storage materials are selected to design the arm structure to control the vibration. Alternatively, the use of damping shock absorbers, damping materials, composite damping metal plates, damping alloys or viscoelastic large damping materials on the flexible beam to form additional damping structures are all passive damping control. In recent years, viscoelastic large damping materials have attracted great attention for vibration control of flexible robotic arms.

5. Force feedback control method. The force feedback control of the vibration of the flexible manipulator is actually a control method based on inverse dynamics analysis, that is, according to the inverse dynamics analysis, the torque applied to the driving end is obtained through the given motion of the end of the arm, and the driving torque is feedback compensated through motion or force detection.

6. Adaptive control. Combined adaptive control is used to divide the system into joint subsystem and flexible subsystem. Adaptive control rules are designed using parameter linearization method to identify the uncertainty parameters of the flexible manipulator. A tracking controller is designed for the flexible manipulator with nonlinearity and parameter uncertainty. The controller is designed based on the robust and adaptive control design of the Lyapunov method. The system is divided into two subsystems through state transition. The two subsystems are controlled by adaptive control and robust control respectively.

7. PID control. As the most popular and widely used controller, PID controller is widely used in rigid robot arm control due to its simplicity, effectiveness and practicality. It is often used to improve the performance of PID controller by adjusting the controller gain to form a self-correcting PID controller or combining it with other control methods to form a composite control system.

8. Variable structure control. Variable structure control system is a discontinuous feedback control system, among which sliding mode control is the most common variable structure control. Its characteristics: on the switching surface, there is a so-called sliding mode, in which the system remains insensitive to parameter changes and disturbances. At the same time, its trajectory is on the switching surface, and the sliding phenomenon does not depend on the system parameters and has a stable nature. The design of the variable structure controller does not require an accurate dynamic model of the robot arm, and the boundaries of the model parameters are sufficient to construct a controller.

9. Fuzzy and neural network control. It is a language controller that reflects the thinking characteristics of people when performing control activities. One of its main characteristics is that the control system design does not require a mathematical model of the controlled object in the usual sense, but requires the operator or expert's experience knowledge, operation data, etc.