Abstract
This paper presents linear active disturbance rejection control (LADRC) for a two-degrees-of-freedom (2-DOF) manipulator system to achieve trajectory tracking. The system is widely used in engineering applications and exhibits the characteristics of high nonlinearity, strong coupling, and large uncertainty with two inputs and two outputs. First, the problem of dynamic coupling in the model of the 2-DOF manipulator is addressed by considering the dynamic coupling, model uncertainties, and external disturbances as total disturbances. Second, a linear extended state observer is designed to estimate the total disturbances, while a linear state error feedback control law is designed to compensate these disturbances. The main contribution is that the stability of the closed-loop system with two inputs and two outputs is analyzed, and the relationship between the performance of the closed-loop system and the controller parameters is established. The joint simulation of SolidWorks and Matlab/Simulink is conducted. The simulation and experimental results clearly indicate the superiority of LADRC over the PID for trajectory tracking and dynamic performance.
Highlights
With the rapid development of automation, manipulators are widely used in industries for applications such as assembling, picking, painting, and welding. erefore, the trajectory tracking control of a manipulator has been widely studied
Focusing on the trajectory tracking control problem of a manipulator system, various control strategies have been studied in related fields, such as PD control with feedforward compensation [3, 4], adaptive control [5,6,7], fuzzy control [8, 9], neural network control [10,11,12,13], and sliding mode control [14]
Ouyang et al [6] proposed an adaptive switching learning PD control (ASLPD), which was a combination of the feedback PD control law with a gain switching technique and the feedforward learning control law with the input torque profile based on interative learning
Summary
With the rapid development of automation, manipulators are widely used in industries for applications such as assembling, picking, painting, and welding. erefore, the trajectory tracking control of a manipulator has been widely studied. (1) A contradiction between system rapidity and overshoot in PID control, which has a limited effect on nonlinear characteristics and time-varying disturbances (2) e adaptive control method requires the control object model to be sufficiently accurate and the tuning of the controller parameters is difficult (3) e structure of fuzzy control and neural network control is complicated and the controller parameters are hard to tune e combination of the control algorithms can make up for the disadvantages of each other to a certain extent; the problem of the complex structure of controllers cannot be solved.
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