Tuesday , October 23 2018

Disturbance-Observer-Based Robust Control of a
Serial-link Robotic Manipulator Using SMC and
PBC Techniques

Syed Ali AJWAD1, Jamshed IQBAL2*, Abdul Attayyab KHAN3, Adeel MEHMOOD1

1 Department of Electrical Engineering,
COMSATS Institution of Information Technology (CIIT), Islamabad, Pakistan
{s.ajwad, adeel.mehmood}@comsats.edu.pk
2 Department of Electrical Engineering,
National University of Computer and Emerging Sciences (FAST-NU), Islamabad, Pakistan
jamshed.iqbal@nu.edu.pk

3 Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS),
University of Genova, Italy
abdul.khan@edu.unige.it

Corresponding author

Abstract: Robotic manipulators deployed in automation industry require high speed with precision and accuracy to perform sophisticated control tasks. Whereas, the factors like highly coupled dynamics, internal and external perturbation forces, joint friction and parameter variations degrade the performance of the manipulator. Consequently, the need of an advanced control technique or more preferably combination of multiple techniques with the capability of handling disturbances has been increased significantly. In the present research, design of Disturbance Observer (DO) based control techniques for a 6-Degree Of Freedom (DOF) robotic arm is presented to eliminate the effect of uncertainties and disturbances and to enhance the robustness of both Sliding Mode Control (SMC) and Passivity Based Control (PBC). Results demonstrate that the proposed controllers precisely estimate the torque yielded by external perturbation forces and improve the trajectory tracking performance of the system, which results in comparatively high performance of robotic manipulator in terms of speed and precision.

Keywords: Robot control, Robotic manipulator, Non-linear control, Industrial robot.

>>Full text<<
CITE THIS PAPER AS:
Syed Ali AJWAD, Jamshed IQBAL, Abdul Attayyab KHAN, Adeel MEHMOOD, Disturbance-Observer-Based Robust Control of a Serial-link Robotic Manipulator Using SMC and PBC Techniques, Studies in Informatics and Control, ISSN 1220-1766, vol. 24 (4), pp. 401-408, 2015.

  1. Introduction

Advancements in the field of automation have significantly accelerated the growth of manufacturing industry. Continuous assembly lines have been implemented to meet the requirement of mass production [1]. Robotic manipulators are considered as an integral part of such production lines as they offer potential advantages like accuracy, repeatability, throughput, swiftness, reliability and safety [2]. Furthermore, they can work in hazardous places where environment is harmful for human health [3]. Robots now perform various jobs ranging from simple task of pick and place to more sophisticated tasks like welding and cutting in automation industry [4]. Moreover, robots are also being extensively employed in the fields of medicine, defense, rescue and safety, mining, underwater and space exploration etc. [5]. Many industrial applications require fast and highly accurate motion of the robots. Precise movement of robotic links with high speed can only be achieved with a well-defined control strategy. Control in robotics refers to the computation of input torque which ensures the accurate tracking of a desired trajectory. Research community has proposed various control strategies ranging from simple linear feedback control e.g. Proportional Integral Derivative (PID) to more sophisticated algorithms. A comprehensive review of such robust and non-linear control strategies has been presented by Ajwad et al. in [6].

Sliding Mode Control (SMC), based on the variable structure control theory, lies in the category of non-linear robust control [7]. The advantages of SMC include system stability and robustness against matched uncertainties. Similarly, Passivity Based Control (PBC) is capable of handling the problems related with tracking and output feedback control. It employs the passivity property of physical system. The robot dynamics are complex and highly nonlinear in nature [8]. The position, velocity and acceleration of one joint have some affect over other joints. Furthermore, modeling uncertainties, friction, gravity and external forces can influence the motion of a robot as well. The performance of designed control technique can be enhanced significantly by adding a Disturbance Observer (DO) in feedback loop which can, substantially, reduce the aforementioned effects. It estimates variations in parameters and friction as external perturbations by using system dynamics.

Realization of control schemes based on DO in the domain of robotics is an active research area. DO has been utilized by Wang et al. in [9] to estimate the friction in a system and to eliminate external disturbances. Tracking performance of LuGre friction model-based motion controller has been improved by adding DO in the feedback loop. He and Xie have implemented DO to control a non-minimum phase system [10]. To compensate the non-linearities and to cater noise in the feedback of system output, another controller comprising of high pass filter has been used. Chen et al. have designed a non-linear DO for 2- Degree Of Freedom (DOF) robotic manipulator in [11] which was further extended for a 3-DOF arm by Korayem and Haghighi in [12]. Stability of the proposed controller has been analyzed through Lyapunov’s stability criterion. It has been demonstrated that non-linear DO based control structure provides superior performance even in the presence of friction and heavy payload. In [13], fast dynamics of tele-operated system, employed in master-slave configuration, has been controlled through DO-based novel control technique. Parameters of the proposed controller determine the minimum rate of exponential convergence and also ensure the boundedness of tracking error even under fast-varying disturbances.

In the present work, DO is implemented to improve the performance of 1st order SMC and PBC for a multi-DOF robotic arm. Both SMC and PBC are subjected to disturbance at input channel. It is shown that DO provides precise estimate of disturbances without any requirement of expensive force and torque sensors. The presence of DO greatly eliminates the effect of disturbances and increases the system robustness.

The remaining paper is organized as follows; Section 2 describes the manipulator system under study with a comprehensive mathematical model.

Section 3 formulates SMC and PBC and presents the tracking results of both techniques. Design of DO and corresponding results have been detailed in Section 4. Finally, Section 5 comments on the conclusion of the paper.

REFERENCES

  1. FLOREA, G., C. LUPU, D. POPESCU, Supervised Solutions for Precise Ratio Control: Applicability in Continuous Production Line, Studies in Informatics and Control, vol. 23(1), 2014, pp. 53-64.
  2. IQBAL, J., R. U. ISLAM, R. U., NABI, A. TAHIR, Robotics for Nuclear Power Plants – Challenges and Future Perspectives, International Conference on Applied Robotics for the Power Industry (CARPI), 2012, pp. 151-156.
  3. BAHR, B., Y. LI, M. NAJAFI, Design and Suction Cup Analysis of a Wall Climbing Robot, Computers & Electrical Engineering, vol. 22(3), 1996, pp. 193-209.
  4. AJWAD, S. A., J. IQBAL, Emerging Trends in Robotics – A Review from Applications Perspective, International Conference on Engineering and Emerging Technologies (ICEET), 2015 (in press).
  5. AJWAD, S. A., J. IQBAL, Recent Advances and Applications of Tethered Robotic Systems, Science International, vol. 26, no. 5, 2014, pp. 2045-2051.
  6. AJWAD, S. A., K. BAIZID, J. IQBAL, M. I. ULLAH, A Comprehensive State-of-the-Art on Control of Industrial Articulated Eobots, Journal of the Balkan Tribological Association, vol. 20, no. 4, 2014, pp. 499-521.
  7. IQBAL, J., R. U. ISLAM, M. F., KHAN, Control Strategies for Robotic Manipulators, IEEE International Conference on Robotics and Artificial Intelligence (ICRAI), 2012, pp. 26-33.
  8. MAI, T., Y. WANG, Adaptive Position Tracking Control System based on Recurrent Fuzzy Wavelet Neural Networks for Robot Manipulators, Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2014.
  9. DING, H., Y. WANG, Z. XIONG, X. ZHU, Nonlinear Friction Compensation and Disturbance Observer for a High-speed Motion Platform, IEEE International Conference on Robotics and Automation (ICRA), 2004, pp. 4515-4520.
  10. HE, Z., W. XIE, Improved Disturbance Observer based Control Structure, Chinese Control and Decision Conference, 2009, pp. 1015-1020.
  11. BALLANCE, D. J., W.-H. CHEN, P. J. GAWTHROP, P. J., J. O’REILLY, A Nonlinear Disturbance Observer for Robotic Manipulators, IEEE Transactions on Industrial Electronics, vol. 47, no. 4, 2000, pp. 932-938.
  12. HAGHIGHI, R., M. H. KORAYEM, Nonlinear Disturbance Observer for Robot Manipulators in 3D Space, Intelligent Robotics and Applications, Springer, 2008, pp. 14-23.
  13. MARQUEZ, H., A. MOHAMMADI, M. TAVAKOLI, Disturbance Observer-based Control of Non-linear Haptic Teleoperation Systems, IET Control Theory and Applications, vol. 5, no. 18, 2011, pp. 2063-2074.
  14. IQBAL, J., U. IQBAL, Z. NISSA, A. SAMAD, Embedded Control System for AUTAREP-A Novel AUTonomous Articulated Robotic Educational Platform, Tehnički vjesnik, vol. 21, no. 6, 2014, pp. 1255-1261.
  15. IQBAL, J., R. U. ISLAM, A. KHALID, S. KHAN, S. MANZOOR, An Autonomous Image-guided Robotic System Simulating Industrial Applications, International Conference on System of Systems Engineering, 2012, pp. 344-349.
  16. AJWAD, S. A., J. IQBAL, R. U. ISLAM, M. I. ULLAH, Modeling Robotic Arms –A Review and Derivation of Screw Theory Based Kinematics, International Conference on Engineering and Emerging Technologies 2014, pp. 98.
  17. IQBAL, J., R. U. ISLAM, H. KHAN, Modeling and Analysis of a 6 DOF Robotic Arm Manipulator, Canadian Journal on Electrical and Electronics Engineering, vol. 3(6), 2012, pp. 300-306.
  18. CRAIG, J. J., Introduction to Robotics: Mechanics and Control, Pearson Prentice Hall: Upper Saddle River, 2005.
  19. MURRAY, R. M., Z. LI, S. S. SASTRY, A Mathematical Introduction to Robotic Manipulation, CRC press, 1994.
  20. IQBAL, J., R. U. ISLAM, A. KHALID, S. MANZOOR, A. SAMAD, An Open-source Multi-DOF Articulated Robotic Educational Platform for Autonomous Object Manipulation, Robotics And Computer-Integrated Manufacturing, vol. 30, no. 3, 2014, pp. 351-362.
  21. EL BAGDOURI, M., S. LAGHROUCHE, A. MEHMOOD, Study of the Nonlinear Control Techniques for Single Acting vgt pneumatic actuator, The International Journal of Vehicle Design, vol. 60, no. 3, 2012, pp. 264-285.
  22. UTKIN, V. I., Sliding Modes in Control and Optimization, Springer-Verlag Berlin, 1992.
  23. CAMPA, R., J. MORENO-VALENZUELA, V. SANTIBÁÑEZ, Model-based Control of a Class of Voltage-Driven Robot Manipulators with Non-passive Dynamics, Computers & Electrical Engineering, vol. 39, no. 7, 2013, pp. 2086-2099.
  24. BASAÑEZ, L., E. NUÑO, R. ORTEGA, Passivity-based Control for Bilateral Teleoperation: A Tutorial, Automatica, vol. 47, no. 3, 2011, pp. 485-495.
  25. MIYACHI, K., M. NAKAO, K. OHNISHI, A Robust Decentralized Joint Control based on Interference Estimation, IEEE International Conference on Robotics and Automation. Proc., 1987, pp. 326-331.
  26. KIM, Y., I. NOH, J. SEOK, S. WON, An Adaptive Disturbance Observer for a Two-link Robot Manipulator, Intl. Conference on Control, Automation and Systems, 2008, pp. 141-145.

https://doi.org/10.24846/v24i4y201504