Home /Research /Experimental evaluation of a saturated output feedback controller using RBF neural networks for SCARA robot IBM 7547
LEARNING

Experimental evaluation of a saturated output feedback controller using RBF neural networks for SCARA robot IBM 7547

Mohammad Pourrahim, Khoshnam Shojaei, Abbas Chatraei, Omid Shah Nazari

Year
2016
Citations
8

Abstract

In this paper, an extension of the passivity-based output feedback trajectory tracking controller is addressed and implemented on a SCARA robot IBM 7547 by using generalized saturation. Compared with the output feedback controllers, a radial basis function saturated observer-based controller has been introduced. The controller will reduce the risk of actuator saturation effectively via generalized saturation functions. Implementation results are provided to illustrate the efficiency of the proposed controller in dealing with the actuator saturation.

Keywords

SCARAControl theory (sociology)Controller (irrigation)ActuatorControl engineeringComputer scienceRobotPID controllerIBMTrajectory

Related papers

Browse all LEARNING papers