Enhancing Disturbance Rejection of PID Controllers for DC Joint Motors of Trajectory Tracking Robots Using Disturbance Observer

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Pinit Ngamsom


In this paper, disturbance rejection of DC motor PID trajectory control systems is enhanced for independent joint control of robot arms. The concept of disturbance observer is invoked to propose a linear auxiliary control that augments existing PID controllers. The design of the auxiliary control is developed using a state space approach rather than transfer function approaches commonly employed in many existing designs derived from the concept of disturbance observer. This provides new insight and leads to a compact design requiring only two design parameters. While many of the existing DC motor trajectory control systems assume the availability of current feedback from a motor coil, the proposed auxiliary control does not. This can highly facilitate its applications in the lacking situation. Realizing that the stability of the resulting control systems could be inconvenient to assert due to increased system dimension resulting from incorporating disturbance observer, compact criteria for asserting robust stability using readily available results is given explicitly. To evaluate the capability of the auxiliary control for disturbance rejection, experimental results on a DC joint motor of an articulated robot arm are given. In presence of smooth and abrupt loading variations due to gravity, it appears that the tracking error of the enhanced system can be approximately 67% of that of the unenhanced system. This result is consistent in all three rounds of experiments.

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How to Cite
Ngamsom, P. (2023). Enhancing Disturbance Rejection of PID Controllers for DC Joint Motors of Trajectory Tracking Robots Using Disturbance Observer. Applied Science and Engineering Progress, 16(4), 6718. https://doi.org/10.14416/j.asep.2023.02.003
Research Articles


F. Nagata and K. Watanabe, Controller Design for Industrial Robots and Machine Tools: Applications to Manufacturing Processes. Wisconsin: Woodhead, 2013, pp. 91–112.

M. Wilson, Implementation of Robot Systems. Amsterdam, Netherlands: Elsevier, 2015, pp. 75–102.

D. G. Caldwell, Robotics and Automation in the Food Industry. Wisconsin: Woodhead, 2013, pp. 21–34.

R. N. Jazar, Theory of Applied Robotics, 2nd ed., Berlin, Germany: Springer, 2010, pp. 838–842.

C. Fallaha, M. Saad, J. Ghommam, and Y. Kali, “Sliding mode control with model-based switching functions applied on a 7-DOF exoskeleton arm,” IEEE/ASME Transactions on Mechatronics, vol. 26, no.1, pp. 539–550, Feb. 2021.

X. Yin and L. Pan, “Enhancing trajectory tracking accuracy for industrial robot with robust adaptive control,” Robotics and Computer-Integrated Manufacturing, vol. 51, pp. 97–102, Jun. 2018.

S. Chen and J. T. Wen, “Industrial robot trajectory tracking control using multi-layer neural networks trained by iterative learning control,” Robotics, vol. 10, no. 1, Mar. 2021, Art. no. 50.

S. Ling, H. Wang, and P. X. Liu, “Adaptive fuzzy tracking control of flexible-joint robots based on command filtering,” IEEE Transactions on Industrial Electronics, vol. 67, no. 5, pp. 4046–4055, May. 2020.

K. Ohishi, K. Ohnishi, and K. Miyachi, “Torque – speed regulation of DC motor based on load torque estimation method,” in International Power Electronics Conference, 1983, pp. 1209–1218.

S. Emre, O. Roberto, and O. Kouhei, “Disturbance observer-based robust control and its applications: 35th anniversary overview,” IEEE Transactions on Industrial Electronics, vol. 67, no. 3, pp. 2042–2053, Mar. 2020.

S. Emre and O. Kouhei, “Stability and robustness of disturbance observer based motion control systems,” IEEE Transactions on Industrial Electronics, vol. 62, no. 1, pp. 414–422, Jan. 2015.

R. Carlson, M. Lajoie-Mazenc, and J. C. d. S. Fagundes, “Analysis of torque ripple due to phase commutation in brushless DC machines,” IEEE Transactions on Industry Applications, vol. 28, no. 3, pp. 632–638, May 1992.

Ramin S. Esfandiari, and B. Lu, Modeling and Analysis of Dynamic Systems, 3rd ed., Florida: CRC Press, 2018, pp. 295–296.

H. K. Khalil, Nonlinear Systems, 3rd ed., New Jersey: Prentice Hall, 2002, pp. 346–350.

S. P. Bhattacharyya, A. Datta, and L. H. Keel, Linear Control Theory: Structure, Robustness, and Optimization. Florida: CRC Press, 2009.

R. K. Yedavalli, Robust Control of Uncertain Dynamic Systems. Berlin, Germany: Springer, 2014, pp. 47–59.

G.-R. Duan, and H.-H. Yu, LMIs in Control Systems. Florida: CRC Press, 2013, pp. 110–119.