Paper
1 May 1996 Feasability of adaptive vibration control of a space truss using modal filters and a neural network
Albert Bosse, Shalom Fisher, Stuart J. Shelley, Tae W. Lim
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Abstract
An adaptive algorithm is proposed for the control of a large space truss structure which uses modal filters for independent modal space control and a simple neural network that provides an on-line system identification capability. The modal filters are computed off-line using measured frequency response functions and estimated pole values for the modes of interest, and provide a coordinate transformation that yields modal coordinates from physical response measurements. The time histories for the modal coordinates are then processed in real time by the neural network, which models a single degree of freedom system transfer function and provides estimates of modal parameters, namely, frequency, damping ratio and modal gain. The modal filters are used to implement independent modal space control on a 3.74 meter space truss using a single reaction-mass actuator and 32 accelerometers. The performance of the modal filter based controller is compared to that of a local rate feedback controller using the same actuator. The applicability of the adaptive filter to adaptive control is demonstrated by real time estimation of the modal parameters of the truss with and without control. Because the modal filter control gain can be adjusted to maintain a desired closed loop damping ratio, which is tracked by the adaptive filter, adaptive control of individual modes in a time-varying system is possible. The goal of this work is to field a control system which can maintain desired closed loop damping ratios for mode frequency variations as high as 10%.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Albert Bosse, Shalom Fisher, Stuart J. Shelley, and Tae W. Lim "Feasability of adaptive vibration control of a space truss using modal filters and a neural network", Proc. SPIE 2717, Smart Structures and Materials 1996: Smart Structures and Integrated Systems, (1 May 1996); https://doi.org/10.1117/12.239061
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Cited by 1 scholarly publication.
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KEYWORDS
Digital filtering

Actuators

Control systems

Neural networks

Sensors

Feedback control

Algorithm development

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