1. Rigid treatment. The effect of elastic deformation of the structure on the motion of the rigid body of the structure is completely ignored. For example, in order to prevent excessive elastic deformation from damaging the stability and terminal positioning accuracy of the flexible robotic arm, NASA's remote-controlled spaceman has a maximum angular velocity of 0.5deg/s.
2. Feedforward compensation method. The mechanical oscillation formed by the flexible deformation of the manipulator arm is regarded as a qualitative disturbance of the rigid motion, and the feedforward compensation method is used to counteract this disturbance. Bernd Gebler from Germany studied feedforward manipulation of industrial robots with elastic rods and elastic joints. Zhang Tiemin discussed the method of eliminating the dominant pole and system instability of the system by adding zeros, and planned a feedforward manipulator with time delay, which can eliminate the residual oscillation of the system more significantly than the PID manipulator.
3. Acceleration response control. Khorrami FarShad and Jain Sandeep discussed the problem of ending trajectory manipulation using the end acceleration response to manipulate a flexible robotic arm.
4. Passive damping control. In order to reduce the influence of the relative elastic deformation of the flexible body, the structure of the planning arm of various energy consumption or energy storage data is selected to control the oscillation. Perhaps the use of damping dampers, damping materials, composite damping metal plates, damping alloys, or viscoelastic large damping materials to form additional damping structures on flexible beams are all classified as passive damping control. In recent years, the application of viscoelastic large damping materials for the oscillation control of flexible robotic arms has attracted great attention.
5. Force response manipulation method. The force response manipulation of the oscillation of the flexible manipulator is actually a manipulation method based on the inverse dynamic analysis, that is, according to the inverse dynamic analysis, the torque exerted on the driving end is obtained through the given motion at the end of the arm, and the driving torque is compensated by motion or force detection.
6. Adaptive control. The combined adaptive control was selected to divide the system into a red joint subsystem and a flexible subsystem. The method of parameter linearization is used to plan adaptive manipulation rules to identify the uncertainty parameters of flexible manipulators. The tracking manipulator was planned for the flexible manipulator with nonlinearity and parameter uncertainty. The planning of the manipulator is based on the robust and adaptive manipulation planning of the Lyapunov method. After the transformation of the situation, the system will be divided into two sub-systems. The two subsystems are manipulated separately with adaptive manipulation and robust manipulation.
7. PID control. As the most popular and widely used controller, PID manipulator is widely used in rigid manipulator control because of its simplicity, usefulness and practicality, and is often composed of self-calibration PID manipulator by adjusting the gain of the manipulator or combined with other control methods to form a composite control system to improve the function of PID manipulator.
8. Variable structure control. The variable structure control system is a discontinuous reaction control system, in which the sliding mode control is the most common variable structure control. Its characteristics: on the switching surface, it has the so-called sliding method, in which the system insists on not being sensitive to parameter changes and disturbances, and at the same time, its trajectory is located on the switching surface, and the sliding phenomenon does not depend on the system parameters, and has stable properties. The planning of the variable structure manipulator does not require an accurate dynamic model of the robotic arm, and the gap in the model parameters is enough to construct a manipulator.
9. Fuzzy and neural network manipulation. It is a language manipulator that can reflect the characteristics of people's thinking when performing manipulative activities. One of its main features is that the planning of the control system does not require a mathematical model of the controlled object in the usual sense, but requires the empirical knowledge and operation data of the operator or expert.
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