Disturbance estimator as a state observer with extended Kalman filter for robotic manipulator

Disturbance Observer‐Based Robot End Constant Contact Force‐Tracking Control

“…e auxiliary variable z is the key to the relationship between sliding mode control and hybrid impedance control. By substituting equation (19) into equation (18) and by eliminating z and _ z in the expression, the following equation is obtained after rearrangement:…”

“…Kawasaki and Ueki [17] proposed a nonlinear disturbance observer without joint angular acceleration to estimate the joint friction and the external force and carried out simulation verification. Agarwal and Parthasarathy [18] used the disturbance observer output as a part of a nonlinear system state variable, treated the output error as an independent Gaussian white noise, and used an extended Kalman filter to track the disturbance. Hu and Xiong [19] compensated the rigid body dynamics model's error with a multilayer perceptron and combined this model with a semiparametric model and a perturbed Kalman filter to improve the accuracy and robustness of force estimation under uncertainty.…”

“…References [10][11][12][13][14][15][16][17][18][19][20][21][22][23] mentioned the use of the disturbance observer to estimate external forces, but the research topics are different from the topics studied in this paper. References [10,11,15] were validated only on two-link robots with simple dynamics models.…”

“…Reference [17] only performed the simulation of the disturbance observer. References [18,20] carried out experimental verifications with robots, but the experimental equipment in Reference [18] is a simple small desktop robot and the experimental equipment in Reference [20] is a pneumatic robot. References [22,23] only performed the simulation based on the combination of sliding mode control and impedance control but did not give an experimental verification.…”

New results on the robust stability of control systems with a generalized disturbance observer

“…[8] DOB, which is proposed in, [9] is a robust control tool used to estimate external disturbance, plant uncertainties, and even plant fault. [10,11] It has been widely employed in industrial applications, such as motion control [12,13] and robot manipulators [14,15] due to its simple structure and powerful capability to reject disturbance. [16,17] Figure 1 shows the block diagram of the standard DOB approach in the industry has resulted in theoretical and systematic analyses and design.…”