Title :
A neuro-fuzzy logic controller for trajectory tracking of uncertain robots
Author :
Tsai, Chih-Hsin ; Liu, Jing-Sin ; Lin, Wei-Song
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
This paper presents an adaptive fuzzy computed-torque controller, that enhances fuzzy controllers with an embedded adjustable two-stages credit assignment and self-learning capability, for uncertain robots, to online track a prescribed trajectory. An adaptation law for the parameters of controller is combined with the dead-zone technique to guarantee a given attenuation region of tracking error in the presence of torque disturbance. Simulations of a two-link robot carrying a heavy load illustrate the effectiveness and attenuation capability of the controller for online trajectory tracking in the presence of inertial parameters uncertainties and torque disturbances
Keywords :
adaptive control; fuzzy control; fuzzy neural nets; neurocontrollers; robots; tracking; uncertain systems; unsupervised learning; adaptive fuzzy computed-torque controller; attenuation region; credit assignment capability; dead-zone technique; embedded adjustable capability; inertial parameters uncertainties; neuro-fuzzy logic controller; online trajectory tracking; self-learning capability; torque disturbance; torque disturbances; tracking error; trajectory tracking; two-link robot; uncertain robots; Adaptive control; Attenuation; Embedded computing; Error correction; Fuzzy control; Logic; Programmable control; Robots; Torque control; Trajectory;
Conference_Titel :
Robotics and Automation, 1996. Proceedings., 1996 IEEE International Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
0-7803-2988-0
DOI :
10.1109/ROBOT.1996.506993
