Vibration control strategies for proof-mass actuators

Proof-mass actuators have been considered for a broad range of structural vibration control problems, from seismic protection for tall buildings to the improvement of metal machining productivity by stabilizing the self-excited vibrations known as chatter. This broad range of potential applications means that a variety of controllers have been proposed, without drawing direct comparisons with other controller designs that have been considered for different applications. This article takes three controllers that are potentially suitable for the machining chatter problem: Direct velocity feedback, tuned-mass-damper control (or vibration absorber control), and active-tuned-mass-damper control (or active vibration absorber control). These control strategies are restated within the more general framework of Virtual Passive Control. Their performance is first compared using root locus techniques, with a model based on experimental data, including the low frequency dynamics of the proof-mass. The frequency response of the test structure is then illustrated under open and closed-loop conditions. The application of the control strategies to avoid machine-tool chatter vibrations is then discussed, without going into detail on the underlying physical mechanisms of chatter. It is concluded that virtual passive absorber control is more straightforward to implement than virtual skyhook damping, and may be better suited to the problem of machining chatter

Explicit integration of differential equations

Explicit integration of differential equation

Reduced-order filtering for flexible space structures

There is a need for feedback control of the large flexible space structures which are going to be increasingly important in the future of the space program. These structures are very lightly damped, and vibrations may persist for a long time when the system is disturbed unless an active feedback control strategy is used to damp out the vibrations. The system is best described by a partial differential equation description, but the more common approach is to use a large set of second order differential equations, where a large number of modes must be retained if the mathematics is to provide an adequate description of the dynamical process. Sensors, such as accelerometers and rate gyros, may provide data to the feedback controller so that it may respond appropriately to control the system. The data from the sensors is not perfect, but is subject to noise, called measurement noise, and the dynamical process itself is subject to disturbances referred to as process noise. Filtering the sensor signals to remove the measurement noise, and using the resulting state estimates to control the system are investigated

Article XX: Entry into Force

Ye

Article XIII: Review of the Protocol

Ye

Preamble

Ye

Article VI: Assistance and Protection against Biological and Toxin Weapons

Ye

Preparing for the BTWC Sixth Review Conference 2006

Ye

Article XXII: Depositary/ies

Ye

Successful Outcomes for the BTWC Sixth Review Conference

Ye