TY - JOUR
T1 - Hybrid computed torque controlled motor-toggle servomechanism using fuzzy neural network uncertainty observer
AU - Lin, Faa Jeng
AU - Wai, Rong Jong
N1 - Funding Information:
The author would like to acknowledge the financial support of the National Science Council of Taiwan, ROC through grant number NSC 89-2213-E-033-048. Moreover, the authors would like to express their gratitudes to the referees and the editor for their kind comments and suggestions.
PY - 2002/10
Y1 - 2002/10
N2 - The dynamic response of a hybrid computed torque controlled toggle mechanism, which is driven by a permanent magnet (PM) synchronous servo motor, is studied in this paper. First, based on the principle of computed torque control, a position controller is developed for the motor-toggle servomechanism. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a fuzzy neural network (FNN) uncertainty observer is utilized to adapt the lumped uncertainty on line. Furthermore, based on the Lyapunov stability a hybrid control system, which combines the computed torque controller, the FNN uncertainty observer and a compensated controller, is proposed to control the position of a slider of the motor-toggle servomechanism. The computed torque controller with FNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rules of the FNN. Finally, simulated and experimental results due to a periodic sinusoidal command show that the dynamic behaviors of the proposed hybrid control system are robust with regard to parametric variations and external disturbances.
AB - The dynamic response of a hybrid computed torque controlled toggle mechanism, which is driven by a permanent magnet (PM) synchronous servo motor, is studied in this paper. First, based on the principle of computed torque control, a position controller is developed for the motor-toggle servomechanism. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a fuzzy neural network (FNN) uncertainty observer is utilized to adapt the lumped uncertainty on line. Furthermore, based on the Lyapunov stability a hybrid control system, which combines the computed torque controller, the FNN uncertainty observer and a compensated controller, is proposed to control the position of a slider of the motor-toggle servomechanism. The computed torque controller with FNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer instead of increasing the rules of the FNN. Finally, simulated and experimental results due to a periodic sinusoidal command show that the dynamic behaviors of the proposed hybrid control system are robust with regard to parametric variations and external disturbances.
KW - Computed torque control
KW - Fuzzy neural network uncertainty observer
KW - Permanent magnet synchronous servo motor
KW - Toggle mechanism
UR - http://www.scopus.com/inward/record.url?scp=0036825877&partnerID=8YFLogxK
U2 - 10.1016/S0925-2312(01)00605-1
DO - 10.1016/S0925-2312(01)00605-1
M3 - 回顧評介論文
AN - SCOPUS:0036825877
SN - 0925-2312
VL - 48
SP - 403
EP - 422
JO - Neurocomputing
JF - Neurocomputing
IS - 1-4
ER -