Universal Robust Adaptive Control of Robot Manipulators Using Real Time Estimation

Abstract This paper proposes an universal adaptive control structure for robot manipulators, without knowing the dynamic model of the system, as well it is robust to corrupt payload change and initial conditions. It considers a simplified model to describe the robot dynamics, instead of the commonly used explicit dynamic model . The simplification allows to largely reduce the number of parameters to be updated. Moreover the simplified model should represent the current system dynamics, which can be ensured by a real time estimation of the model parameters. In this case, the corrupt change of payload will be detected within short time window such as 0.1 second, and the system dynamics will be adjusted quickly to real values. Modulating functions techniques are also applied on the real time estimation process, to decrease the order of input via integration by part method, which avoids using joint velocities and accelerations. Meanwhile the filtering property of modulating functions are studied so that groups of modulating functions are selected in order to eliminate the high frequency noise influence. In the end simulation results on a two degrees of freedom planar robot prove the control structure eficient.

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