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Regressor-free prescribed performance robot tracking

Published online by Cambridge University Press:  29 May 2013

Y. Karayiannidis*
Affiliation:
Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, Royal Institute of Technology (KTH), SE-100 44 Stockholm, Sweden
Z. Doulgeri
Affiliation:
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece
*
*Corresponding author. E-mail: [email protected]

Summary

Fast and robust tracking against unknown disturbances is required in many modern complex robotic structures and applications, for which knowledge of the full exact nonlinear system is unreasonable to assume. This paper proposes a regressor-free nonlinear controller of low complexity which ensures prescribed performance position error tracking subject to unknown endogenous and exogenous bounded dynamics assuming that joint position and velocity measurements are available. It is theoretically shown and demonstrated by a simulation study that the proposed controller can guarantee tracking of the desired joint position trajectory with a priori determined accuracy, overshoot and speed of response. Preliminary experimental results to a simplified system are promising for validating the controller to more complex structures.

Type
Articles
Copyright
Copyright © Cambridge University Press 2013 

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References

1.Spong, M. W., Hutchinson, S. and Vidyasagar, M., Robot Modelling and Control (John Wiley, Somerset, New Jersey, 2006).Google Scholar
2.Slotine, J. and Li, W., Applied Nonlinear Control (Prentice Hall, Upper Saddle River, New Jersey, 1993).Google Scholar
3.Sage, H., Mathelin, M. D. and Ostertag, E., “Robust control of robot manipulators: A survey,” Int. J. Control 72, 14981522 (1999).CrossRefGoogle Scholar
4.Lewis, F., Jagannathan, S. and Yeşildirek, A., Neural Netwrok Control of Robot Manipulators and Nonlinear Systems (Taylor & Francis, Boca Raton, Florida, 1999).Google Scholar
5.Kawamura, S., Miyazaki, F. and Arimoto, S., “Is a Local Linear PD Feedback Control Law Effective for Trajectory Tracking of Robot Motion?,” In: Proceedings of the IEEE International Conference in Robotics and Automation, Philadelphia (1988) pp. 13351340.Google Scholar
6.Wen, J. and Murphy, S., “PID Control for Robot Manipulators,” CIRSSE Document #54 (Rensselaer Polytechinc Institute, Troy, New York, May 1990).Google Scholar
7.Qu, Z. and Dorsey, J., “Robust PID control of robots,” Int. J. Robot. Autom. 6 (4), 228235 (1991).Google Scholar
8.Lugo-Villeda, L., Frisoli, A., Parra-Vega, V. and Bergamasco, M., “Regressor-Free Force/Position Control of Fixed-Base Exoskeletons for Rehabilitation Tasks,” In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009 (IROS 2009), St. Louis (Oct. 2009) pp. 16391645.CrossRefGoogle Scholar
9.Yao, B. and Tomizuka, M., “Adaptive robust motion and force tracking control of robot manipulators in contact with stiff surfaces,” ASME J. Dyn. Syst. Meas. Control, 120, 232240 (1998).CrossRefGoogle Scholar
10.Hackl, C. M., Endisch, C. and Schröder, D., “Contributions to non-identifier based adaptive control in mechatronics,” Robot. Auton. Syst. 57 (10), 9961005 (2009).CrossRefGoogle Scholar
11.Bechlioulis, C. and Rovithakis, G., “Prescribed performance adaptive control for multi-input multi-output affine in the control nonlinear systems,” IEEE Trans. Autom. Control 55 (5), 12201226 (2010).CrossRefGoogle Scholar
12.Bechlioulis, C., Doulgeri, Z. and Rovithakis, G., “Robot Force/Position Tracking with Guaranteed Prescribed Performance,” In: Proceedings of the IEEE International Conference in Robotics and Automation, Kobe (2009), pp. 36883693.Google Scholar
13.Doulgeri, Z., Karayiannidis, Y. and Zoidi, O., “Prescribed Performance Control for Robot Joint Trajectory Tracking Under Parametric and Model Uncertainties,” In: Proceedings of the IEEE 17th Mediterranean Conference on Control and Automation, Thessaloniki (2009) pp. 13131318.Google Scholar
14.Doulgeri, Z. and Zoidi, O., “Prescribed Performance Regulation for Robot Manipulators,” In: Proceedings of the 9th International IFAC Symposium on Robot Control (SYROCO ‘09), Gifu (2009) pp. 721726.Google Scholar
15.Doulgeri, Z. and Karayiannidis, Y., “PID Type Robot Joint Position Regulation with Prescribed Performance Guaranties,” In: Proceedings of the IEEE International Conference in Robotics and Automation, Anchorage (2010) pp. 41374142.Google Scholar
16.Doulgeri, Z. and Droukas, L., “Robot Task Space PID Type Regulation with Prescribed Performance Guaranties,” In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei (2010) pp. 16441649.Google Scholar
17.Karayiannidis, Y. and Doulgeri, Z., “Model-free robot joint position regulation and tracking with prescribed performance guarantees,” Robot. Auton. Syst. 60 (2), 214226 (2012).CrossRefGoogle Scholar
18.Kelly, R., Santibáñez, V. and Loría, A., Control of Robot Manipulators in Joint Space (Springer, New York, 2005).Google Scholar
19.Bechlioulis, C. and Rovithakis, G., “Robust adaptive control of feedback linearizable mimo nonlinear systems with prescribed performance,” IEEE Trans. Autom. Control 53 (9), 20902099 (2008).CrossRefGoogle Scholar
20.Arimoto, S., Control Theory of Non-linear Mechanical Systems, A Passivity-Based and Circuit-Theoretic Approach (Oxford University Press, Oxford, UK, 1996).CrossRefGoogle Scholar
21.Khalil, H., Nonlinear Systems, 3rd ed. (Prentice Hall, Upper Saddle River, New Jersey, 2002).Google Scholar
22.Siciliano, B., Sciavicco, L., Villani, L. and Oriolo, G., Robotics: Modelling, Planning and Control (Springer-Verlag, Berlin, Germany, 2009).CrossRefGoogle Scholar