A new robust indirect adaptive control for torque-driven robot manipulators under relaxed excitation conditions

https://doi.org/10.58571/CNCA.AMCA.2024.087

Resumen: This paper presents a new robust adaptive joint position trajectory tracking control for torque-driven robot manipulators using a novel parameter identification scheme. The novelty of this identification scheme is that ensures convergence of the true parameters exponentially, even when the regressor do not verify the stringent condition of persistent excitation, using a classical normalized gradient descendent adaptive law. An indirect adaptive controller approach is used to combine the identification scheme with a robust model based GES controller to verify joint position trajectory tracking control objectives under constant disturbances. The validity of our claims are illustrated with simulations of a two degrees-offreedom robot manipulator.

¿Cómo citar?

Cervantes Pérez, L., Santibanez, V. & Sandoval, J. (2024). A new robust indirect adaptive control for torque-driven robot manipulators under relaxed excitation conditions. Memorias del Congreso Nacional de Control Automático 2024, pp. 511-517. https://doi.org/10.58571/CNCA.AMCA.2024.087

Palabras clave

Parameter estimation, Estimation algorithms, Euler-Lagrange systems, Passivity-based control

• Abouelsoud, A.A., Hassan, M.F., and Sultan, M.A. (1996). An adaptive observer for robots with persistent excitation. International journal of systems science, 27(9), 809-820.
• Aranovskiy, S., Bobtsov, A., Ortega, R., and Pyrkin, A. (2017). Performance enhancement of parameter estimators via dynamic regressor extension and mixing. IEEE Transactions on Automatic Control, 62(7), 3546-3550.
• Armstrong, B. (1987). On finding exciting trajectories for identification experiments involving systems with non-linear dynamics. In Proceedings. 1987 IEEE International Conference on Robotics and Automation, volume 4, 1131-1139. IEEE.
• Arteaga, M.A. (2023). On the exact parameter estimation for robot manipulators without persistence of excitation. IEEE Transactions on Automatic Control.
• Arteaga, M.A. (2024). On the exact parameter estimation of robot manipulators with a predefined minimal amount of excitation. International Journal of Robust and Nonlinear Control.
• Åström, K.J. and Wittenmark, B. (2008). Adaptive control. Courier Corporation.
• Bastin, G. and Dochain, D. (eds.) (1990). On-line Estimation and Adaptive Control of Bioreactors. Process Measurement and Control. Elsevier.
• Bobtsov, A., Yi, B., Ortega, R., and Astolfi, A. (2022). Generation of new exciting regressors for consistent online estimation of unknown constant parameters. IEEE Transactions on Automatic Control, 67(9), 4746-4753.
• De Wit, C.C. and Aubin, A. (1990). Parameters identification of robots manipulators via sequential hybrid estimation algorithms. IFAC Proceedings Volumes, 23(8), 163-168.
• Hsu, P., Bodson, M., Sastry, S., and Paden, B. (1987). Adaptive identification and control for manipulators without using joint accelerations. In Proceedings. 1987 IEEE International Conference on Robotics and Automation, volume 4, 1210-1215. IEEE.
• Kozlowski, K.R. and Dutkiewicz, P. (1996). Experimental identification of robot and load dynamics. IFAC Proceedings Volumes, 29(1), 397-402.
• Landau, I.D., Lozano, R., M’Saad, M., and Karimi, A. (2011). Adaptive control: algorithms, analysis and applications. Springer Science & Business Media. Ortega, R., Bobtsov, A., Nikolaev, N., Schiffer, J., and Dochain, D. (2021). Generalized parameter estimationbased observers: Application to power systems and chemical-biological reactors. Automatica, 129, 109635.
• Ortega, R., Loría, A., Nicklasson, P.J., and Sira-Ramírez, H. (1998). Passivity-based control of euler-lagrange systems: mechanical, electrical and electromechanical applications. Springer London.
• Perreault, G., Roess, T.L., and Powell, F.D. (1972). Submarine Parameter Identification. Bell Aerospace Company.
• Prufer, M., Schmidt, C., and Wahl, F. (1994). Identification of robot dynamics with differential and integral models: a comparison. In Proceedings of the 1994 IEEE international conference on robotics and automation, 340-345. IEEE.
• Romero, J.G., Ortega, R., and Bobtsov, A. (2023). Parameter estimation and adaptive control of euler-lagrange systems using the power balance equation parameterisation. International Journal of Control, 96(2), 475-487.
• Sandoval, J., Cervantes-Pérez, L., Santibáñez, V., Moreno-Valenzuela, J., and Kelly, R. (2023). A ges joint position trajectory tracking smooth controller of torque-driven robot manipulators affected by disturbances. International Journal of Robust and Nonlinear Control.
• Sastry, S. and Bodson, M. (2011). Adaptive Control: Stability, Convergence and Robustness. Dover Books on Electrical Engineering Series. Dover Publications.
• Schafroth, D., Bermes, C., Bouabdallah, S., and Siegwart, R. (2010). Modeling, system identification and robust control of a coaxial micro helicopter. Control Engineering Practice, 18(7), 700{711. Special Issue on Aerial Robotics.
  Slotine, J.J.E. and Li, W. (1989). Composite adaptive control of robot manipulators. Automatica, 25(4), 509-519.
• Tao, G. (2003). Adaptive control design and analysis, volume 37. John Wiley & Sons.
  Yarza, A., Santibanez, V., and Moreno-Valenzuela, J. (2013). An adaptive output feedback motion tracking controller for robot manipulators: Uniform global asymptotic stability and experimentation. International Journal of Applied Mathematics and Computer Science, 23(3), 599-611.