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Motor Control Based on Disturbance Observer and Adaptation Algorithm
Motor Control Based on Disturbance Observer and Adaptation Algorithm
K. Ohnishi concluded that the conventional installation of sensor elements requires filtering and other processing, which is not convenient for practical applications. Therefore, they developed a Reaction Torque Observer (RTO) with force sensing feedback, which was used in a 6-axis industrial robot, by combining the characteristics of external disturbance observer to estimate the external force, and showed that this sensorless control can obtain the force value more easily.[1] B. Yalcin and K. Ohnishi used an external disturbance observer and a reaction force observer to implement Impedance Control, and combined it with Sliding Model Neural Network Control to quickly correct the environmental forces sensed by the robot.[2]
The reasons for selecting the Disturbance Observer in this research are as follows.
1.Compared with other anti-disturbance controllers, the parameters are simple and easy to design.
2.The inner loop and the outer loop can be designed separately, which has a high design freedom.
3. Decoupled by negative feedback, easy to understand and intuitive.
4. The characteristics of external disturbance can be estimated, and sensorless control can be used.
Citation
[1] S. Katsura, Y. Matsumoto and K. Ohnishi, "Modeling of Force Sensing and Validation of Disturbance Observer for Force Control," in IEEE Transactions on Industrial Electronics, vol. 54, no. 1, pp. 530-538, Feb. 2007, doi: 10.1109/TIE.2006.885459.
[2] B. Yalcin and K. Ohnishi, "Environmental Impedance Estimation and Imitation in Haptics by Sliding Mode Neural Networks," IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics, 2006, pp. 4014-4019, doi: 10.1109/IECON.2006.347716.
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