Title :
Fuzzy adaptive noise filtering and vibration control for a flexible robot
Author :
Green, A. ; Sasiadek, J.Z.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Carleton Univ., Ottawa, Ont., Canada
Abstract :
End effector tracking of a two-link flexible robot is simulated using a linear quadratic Gaussian (LQG) dynamic regulator with an extended Kalman filter (EKF), a LQG with fuzzy logic adaptive EKF (FLAEKF), LQG with an EKF and a FLAEKF combined with time delays in the feedback loop to model nonminimum phase (NMP) response for a sensor noncollocated at the end effector and in the feed forward loop for corrective control action. A fuzzy logic system (FLS) vibration suppression control strategy is simulated for comparison. Results demonstrate FLS adaptive vibration suppression produces greater tracking accuracy than an EKF, FLAEKF or corrective time delays. In comparison with classical FID control or even with more advanced adaptive control strategies FLS vibration suppression gives better tracking control while execution time remains acceptable.
Keywords :
Kalman filters; adaptive control; delays; end effectors; feedforward; fuzzy control; fuzzy logic; linear quadratic Gaussian control; nonlinear dynamical systems; vibration control; FID control; LQG dynamic regulator; adaptive control; adaptive vibration suppression; corrective control action; end effector tracking; feed forward loop; feedback loop; fuzzy adaptive noise filtering; fuzzy logic adaptive extended Kalman filter; fuzzy logic system; linear quadratic Gaussian; noncollocated sensor; nonminimum phase response model; time delays; tracking control; two-link flexible robot; vibration control; vibration suppression control; Adaptive control; Adaptive filters; Delay effects; End effectors; Filtering; Fuzzy control; Fuzzy logic; Programmable control; Robots; Vibration control;
Conference_Titel :
Robot Motion and Control, 2005. RoMoCo '05. Proceedings of the Fifth International Workshop on
Print_ISBN :
83-7143-266-6
DOI :
10.1109/ROMOCO.2005.201445