Due to the increase in the flexibility effect of joints and linkages during motion, the structure is deformed thus making the task execution less accurate. Therefore, the structural flexibility characteristics of the robot arm must be considered, and the system dynamics must also be considered to achieve high precision and effective control of the flexible robot arm. The flexible robotic arm is a very complex dynamical system, and its dynamical equations are nonlinear, strongly coupled, and real-variable. The study of the dynamics of the flexible arm is extremely important to establish the model.
The flexible robotic arm is not only a rigid-flexible coupled nonlinear system, but also a nonlinear system in which the dynamics characteristics of the system and the control characteristics are coupled with each other, i.e., electromechanical coupling. The purpose of dynamics modeling is to provide a basis for control system description and controller design. The general control system description (including state space description in the time domain and transfer function description in the frequency domain) is closely related to the positioning of the sensor/actuator, the information transfer from the actuator to the sensor, and the dynamics of the robotic arm.
The control of the flexible robotic arm is generally performed in the following ways.
1. Rigidization process: The effect 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 to destroy the stability and end positioning accuracy of the flexible robotic arm, the maximum angular velocity of NASA's remote control space hand motion is 0.5deg/s.
2, feedforward compensation method: the mechanical vibration formed by the flexible deformation of the robot arm is seen as a deterministic interference to the rigid motion and the feedforward compensation is used to offset this interference. Bernd Gebler of Germany studied the feedforward control of industrial robots with flexible rods and flexible joints. Tie-Min Zhang studied the method based on the use of increasing the zero point to eliminate the dominant pole of the system and system instability, and designed the feedforward controller with time delay, which can eliminate the residual vibration of the system more obviously when compared with the PID controller.Seering Warren P. and other scholars have conducted an in-depth study on the feedforward compensation technology.
3, acceleration feedback control: Khorrami FarShad and Jain Sandeep studied the use of end acceleration feedback to control the end trajectory control problem of flexible robotic arm.
4, passive damping control: To reduce the effect of the relative elastic deformation of the flexible body Various energy dissipating or energy storing materials are selected to design the structure of the arm to control the vibration. Or in the flexible beam using damping dampers, damping materials, composite damping metal plate, damping alloy or with viscoelastic large damping materials to form additional damping structure are passive damping control. In recent years, the use of viscoelastic large damping materials for the vibration control of flexible robotic arms has attracted great attention. rossi Mauro and Wang David studied the passive control of flexible robots.
5, force feedback control method: force feedback control of flexible robotic arm vibration is actually a control method based on inverse dynamics analysis, that is, according to inverse dynamics analysis, the moment applied to the drive end is obtained from a given motion at the end of the arm, and the drive moment is compensated by feedback through motion or force detection.
6、Adaptive control: Combined adaptive control is used to divide the system into joint subsystem and flexible subsystem. The adaptive control rules are designed to identify the uncertain parameters of the flexible robotic arm by using the parameter linearization method. A tracking controller is designed for the flexible robotic arm with nonlinearity and parameter uncertainty. The controller is designed based on the robust and adaptive control design of Lyapunov method. The system is divided into two subsystems by state transition. The two subsystems are controlled by adaptive control and robust control respectively.
7, PID control: PID controller as the most popular and widely used controller, due to its simple, effective and practical, is commonly used for rigid robotic arm control, often by adjusting the controller gain to form a self-correcting PID controller or combined with other control methods to form a composite control system to improve the performance of the PID controller.
8, variable structure control: variable structure control system is a discontinuous feedback control system, of which sliding mode control is the most common variable structure control. Its characteristics: on the switching surface, with the so-called sliding mode, in the sliding mode the system is insensitive to parameter changes and perturbations remain, at the same time, its trajectory is located on the switching surface, the sliding phenomenon does not depend on the system parameters and has a stable nature. The design of variable structure controller does not require an accurate dynamic model of the robot arm, and the boundary of the model parameters is sufficient to construct a controller.
9, fuzzy and neural network control: is a linguistic controller, which can reflect the characteristics of human thinking when performing control activities. One of its main features is that the control system design does not require a mathematical model of the controlled object in the usual sense, but the empirical knowledge of the operator or expert, operational data, etc.
