Stuart J. Shelley

Health monitoring of flexible structures using modal filter concepts

This paper develops an approach for the health monitoring of a smart structures with multiple embedded sensing and actuation capability. For such a structure the consideration of failure consequences is an important component of any real application. The approach developed here is an integrated control and monitoring procedure whereby the sensors, which are assumed to be distributed spatially across the structure, are processed by a set of spatial modal filters which automatically track the modal coordinates of desired, specified modes, and similarly track changes in modal characteristics such as modal frequency, damping, and mode shape. The adaptive modal filter is formulated and applied to tr:a.ck the time varying behavior of specified modes, thereby indicating in some general sense, the health of the structural system. The adaptive modal filter is insensitive to failures or calibration shifts in individual sensors and will automatically ignore failed sensors. It can also be used to detect disturbances entering the system as well as to identify failed actuator locations. A modal controller based on these estimates is then able to adapt to a changing structure and in addition is insensitive to failures in the sensors and actuators. Both the tl1eory and experimental results from a test structure is discussed.

Modal Filters and Neural Networks for Adaptive Vibration Control

An adaptive control algorithm is investigated for the vibration suppression of a space truss structure using modal filters for independent modal space control and a neural network for online system identification. The modal filters are computed off-line using measured frequency response functions and estimated pole values for the modes of interest. They are used to conduct transformation of response measurements from physical coordinates to modal coordinates. The time histories in the modal coordinates are then processed in real time by the neural network to extract estimates of modal parameters, namely, natural frequency, damping ratio, and modal gain. To examine the performance of the adaptive control approach, a controller was designed using the modal filters and implemented on a laboratory 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 neural network to adaptive control was 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 neural network, adaptive control of individual modes in a time-varying system is possible. Eventually, this type of adaptive controller will help develop a control system that can maintain desired closed- loop performance characteristics under significant modal parameter variations.

Feasability of adaptive vibration control of a space truss using modal filters and a neural network

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%.

Simulation of combined adaptive feedforward and spatio-temporal control of an Earth observing telescope

An active vibration control method incorporating a spatio-temporal filter (STF) and an adaptive feedforward controller is presented as an approach to meet the motion stability requirements for next generation, segmented, optical space systems. In such systems, pointing accuracy must be maintained under conditions that include periodic disturbances such as those induced by the Reaction Wheel Actuators (RWA). When a tachometer signal is available, it can be used in an adaptive feedforward control scheme to cancel the periodic disturbance in the output. A model for the RWA is used that includes harmonics that can excite the flexible modes of the system. The STF controller can be used to increasing damping on these modes, thereby allowing for higher gains and quicker convergence by the feedforward controller. Here, this control method is applied to a state-space model of AFRLs Deployable Optical Telescope (DOT), where the control goal is to maintain the mirror positions while undergoing an RWA disturbance.

Control of the ultraLITE precision deployable test article using adaptive spatio-temporal-filtering-based control

Experimental results are presented for active vibration control of the Air Force Research Laboratorys UltraLITE Precision Deployable Optical Structure (PDOS), a ground based model of a sparse array, large aperture, deployable optical space telescope. The primary vibration suppression technique employs spatio-temporal filtering, in which a small number of sensors are used to produce modal coordinates for the structural modes to be controlled. The spatio-temporal filtering technique is well suited for the control of complex, real-world structures because it requires little model information, automatically adapts to sensor and actuator failures, is computationally efficient, and can be easily configured to account for time-varying system dynamics. While controller development for PDOS continues, the results obtained thus far indicate the need for an integrated optical/structural control system.