TY - JOUR
T1 - Tracking of periodic oscillations in an underactuated system via adaptive neural networks
AU - Puga-Guzmán, Sergio A.
AU - Aguilar-Avelar, Carlos
AU - Moreno-Valenzuela, Javier
AU - Santibáñez, Víctor
N1 - Publisher Copyright:
© The Author(s) 2018.
PY - 2018/3/1
Y1 - 2018/3/1
N2 - In this paper, the tracking control of periodic oscillations in an underactuated mechanical system is discussed. The proposed scheme is derived from the feedback linearization control technique and adaptive neural networks are used to estimate the unknown dynamics and to compensate uncertainties. The proposed neural network-based controller is applied to the Furuta pendulum, which is a nonlinear and nonminimum phase underactuated mechanical system with two degrees of freedom. The new neural network-based controller is experimentally compared with respect to its model-based version. Results indicated that the proposed neural algorithm performs better than the model-based controller, showing that the real-time adaptation of the neural network weights successfully estimates the unknown dynamics and compensates uncertainties in the experimental platform.
AB - In this paper, the tracking control of periodic oscillations in an underactuated mechanical system is discussed. The proposed scheme is derived from the feedback linearization control technique and adaptive neural networks are used to estimate the unknown dynamics and to compensate uncertainties. The proposed neural network-based controller is applied to the Furuta pendulum, which is a nonlinear and nonminimum phase underactuated mechanical system with two degrees of freedom. The new neural network-based controller is experimentally compared with respect to its model-based version. Results indicated that the proposed neural algorithm performs better than the model-based controller, showing that the real-time adaptation of the neural network weights successfully estimates the unknown dynamics and compensates uncertainties in the experimental platform.
KW - Furuta pendulum
KW - Tracking control
KW - adaptive neural network
KW - periodic oscillation
KW - real-time experiments
UR - http://www.scopus.com/inward/record.url?scp=85053607468&partnerID=8YFLogxK
U2 - 10.1177/1461348417752988
DO - 10.1177/1461348417752988
M3 - Artículo
SN - 1461-3484
VL - 37
SP - 128
EP - 143
JO - Journal of Low Frequency Noise Vibration and Active Control
JF - Journal of Low Frequency Noise Vibration and Active Control
IS - 1
ER -