Jun Oh Jang

Learn More
A deadzone compensator is designed for an XY -positioning table using fuzzy logic. The classification property of fuzzy-logic systems makes them a natural candidate for the rejection of errors induced by the deadzone, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy-logic parameters, so that the(More)
A friction and output backlash compensator is designed for systems by the fuzzy logic (FL) and the neural network (NN). The classification property of FL system and the function approximation ability of the NN make them the natural candidate for the rejection of errors induced by the friction and output backlash. The tuning algorithms are given for the(More)
  • Jun Oh Jang
  • Journal of Intelligent and Robotic Systems
  • 2011
A control structure that makes possible the integration of a kinematic controller and a neuro-fuzzy network (NFN) dynamic controller for mobile robots is presented. A combined kinematic/dynamic control law is developed using backstepping and stability is guaranteed by Lyapunov theory. The NFN controller proposed in this work can deal with unmodeled bounded(More)
A backlash compensator is designed for nonlinear systems using the fuzzy logic. The classification property of fuzzy logic systems makes them a natural candidate for the rejection of errors induced by the backlash, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy logic parameters, so that the backlash compensation(More)
This paper presents control designs using an neuro-fuzzy network. (NFN) for il XY positioning table. The neuro-furzy controller is composed of an outer PD tracking loop for stabilization of the fast flexible mode dynamics and an NFN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NFN parameters so that the(More)
A saturation and deadzone compensator is designed for systems by the fuzzy logic (FL) and the neural network (NN). The classification property of the FL system and the function approximation ability of the NN make them the natural candidate for the rejection of errors induced by the saturation and deadzone. The tuning algorithms are given for the fuzzy(More)
  • 1