Structural Vibration Suppression by a Neural-Network Controller with a Mass-Damper Actuator

PID and LQR/LQG controllers have are known to be ineffective for systems suffering from parameter variations and broadband excitations. This paper presents a neural-network design for system identification and vibration suppression in a building structure with an active mass-damper. It is shown both numerically and experimentally that the neural-network controller can reliably identify system dynamics and effectively suppress vibration. For the experimental model, which has a fundamental frequency of about 0.96 Hz, the steady-state vibration amplitude under resonance and random excitation are reduced by 80% and 70%, respectively. In addition, the peak-to-peak displacement under the 7.1 Richer scale Ji-Ji earthquake, Taiwan (Sep. 21, 1999) is effectively reduced by 80%. The controller is also shown to be robust to variations in system parameters.

[1]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[2]  G. S. Lee,et al.  Vibration Control of Smart Structures by Using Neural Networks , 1997 .

[3]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[4]  S. M. Yang,et al.  An Optimal Neural Network Design Methodology for Fast Convergence and Vibration Suppression , 1998 .

[5]  A. K. Rigler,et al.  Accelerating the convergence of the back-propagation method , 1988, Biological Cybernetics.

[6]  Dean T. Mook,et al.  Neural‐network control of building structures by a force‐matching training scheme , 1999 .

[7]  Faryar Jabbari,et al.  H∞ Control for Seismic-Excited Buildings with Acceleration Feedback , 1995 .

[8]  Chih-Chen Chang,et al.  A simple optimal pole location technique for structural control , 1998 .

[9]  Jenq-Neng Hwang,et al.  Attentional focus training by boundary region data selection , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[10]  Yu-Ao He,et al.  Control of structural seismic response by self-recurrent neural network (SRNN) , 1998 .

[11]  Jamshid Ghaboussi,et al.  Active Control of Structures Using Neural Networks , 1995 .

[12]  Robert A. Jacobs,et al.  Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[13]  Fereidoun Amini,et al.  Neural Network for Structure Control , 1995 .

[14]  Isao Nishimura.  Acceleration feedback method applied to active tuned mass damper , 1992, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.