Abstract
The problem of the manipulator hybrid position/force control is not trivial because the manipulator is a nonlinear object, whose parameters may be unknown, variable and the working conditions are changeable. The neural control system enables the manipulator to behave correctly, even if the mathematical model of the control object is unknown. In this paper, the hybrid position/force controller with a neural compensation of nonlinearities for the SCORBOT-ER 4pc robotic manipulator is presented. The presented control law and adaptive law guarantee practical stability of the closed-loop system in the sense of Lyapunov. The results of a numerical simulation are presented.
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Gierlak, P. (2012). Hybrid Position/Force Control of the SCORBOT-ER 4pc Manipulator with Neural Compensation of Nonlinearities. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_52
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DOI: https://doi.org/10.1007/978-3-642-29350-4_52
Publisher Name: Springer, Berlin, Heidelberg
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