Abstract
In this paper, we propose a novel adaptive control scheme for robotic systems by incorporating the parameter error into the adaptive law. By carrying out filter operations, the robotic system is linearly parameterized without using the measurements of acceleration. Then a new adaptive algorithm is introduced to guarantee that the parameter error and control error exponentially converge to zero. In particular, we provide an intuitive method to verify the standard PE condition for the parameter estimation. The robustness against disturbances is also studied and comparisons to several adaptive laws are provided. Simulations with a realistic robot arm are presented to validate the improved performance.
*This work was supported by the National Natural Science Foundation of China (No. 61203066).
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References
Sastry S, Bodson M (1989) Adaptive control: stability, convergence, and robustness. Prentice Hall, New Jersey
Ioannou PA, Sun J (1996) Robust adaptive control. Prentice Hall, New Jersey
Slotine JJE, Li W (1989) Composite adaptive control of robot manipulators. Automatica 25(4):509–519
Patre PM, MacKunis W, Johnson M, Dixon WE (2010) Composite adaptive control for Euler-Lagrange systems with additive disturbances. Automatica 46(1):140–147
Adetola V, Guay M (2010) Performance improvement in adaptive control of linearly parameterized nonlinear systems. IEEE Trans Autom Control 55(9):2182–2186
Na J, Herrmann G, Ren X, Mahyuddin MN, Barber P (2011) Robust adaptive finite-time parameter estimation and control of nonlinear systems. In: Proceeding of IEEE international symposium on intelligent control (ISIC), Denver, CO, USA, pp 1014–1019
Na J, Mahyuddin MN, Herrmann G, Ren X (2013) Robust adaptive finite-time parameter estimation for linearly parameterized nonlinear systems. In: Proceeding of 2013 32nd Chinese control conference (CCC), pp 1735–1741
Na J, Ren X, Xia Y (2014) Adaptive parameter identification of linear SISO systems with unknown time-delay. Syst Control Lett 66:43–50
Lewis FL, Liu K, Yesildirek A (2002) Neural net robot controller with guaranteed tracking performance. IEEE Trans Neural Netw 6(3):703–715
Wang L, Chai T, Zhai L (2009) Neural-network-based terminal sliding-mode control of robotic manipulators including actuator dynamics. IEEE Trans Ind Electron 56(9):3296–3304
Lewis FL, Dawson DM, Abdallah CT (2004) Robot manipulator control: theory and practice, vol 15. Marcel Dekker Inc, New York
Mahyuddin M, Herrmann G, Khan S (2012) A Novel adaptive control algorithm in application to a humanoid robot arm. Adv Auton Robot 7429:25–36
Na J, Mahyuddin MN, Herrmann G, Ren X, Barber P (2014) Robust adaptive finite time parameter estimation and control for robotic systems. Int J Robust Nonlinear Control, pp 1–27 (In press)
Craig JJ (2005) Introduction to robotics: mechanics and control vol 3. Pearson Prentice Hall, Upper Saddle River
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Jing, B., Na, J., Gao, G., Sun, G. (2016). Robust Adaptive Control for Robotic Systems with Guaranteed Parameter Estimation. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48386-2_36
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DOI: https://doi.org/10.1007/978-3-662-48386-2_36
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