Person:
Craig,
James I.
Craig,
James I.
Permanent Link
Associated Organization(s)
Organizational Unit
ORCID
ArchiveSpace Name Record
12 results
Publication Search Results
Now showing
1 - 10 of 12
-
ItemAdaptive control of a slender launch vehicle(Georgia Institute of Technology, 2010-12-30) Calise, Anthony J. ; Craig, James I.
-
ItemGSRP/Graybeal: Model verification and decentralized adaptive control of solar ...(Georgia Institute of Technology, 2007-08-21) Craig, James I. ; Graybill, Nathan W. ; Whorton, Mark S.
-
ItemAdaptive Control for a Microgravity Vibration Isolation System(Georgia Institute of Technology, 2005) Yang, Bong-Jun ; Calise, Anthony J. ; Craig, James I. ; Whorton, Mark S.Most active vibration isolation systems that try to a provide quiescent acceleration environment for space-science experiments have utilized linear design methods. In this report, we address adaptive control augmentation of an existing classical controller that combines a high-gain acceleration inner-loop feedback together with a low-gain position outer-loop feedback to regulate the platform about its center position. The control design considers both parametric and dynamic uncertainties because the isolation system must accommodate a variety of payloads having different inertial and dynamic characteristics. We show how adaptive control is beneficial in three important aspects in design of a controller for uncertain systems: performance, robustness, and transient responses. First, performance is treated in the setting that an accelerometer and an actuator is located at the same location, as is the current hardware configuration for g-LIMIT. Second, robustness for the control system becomes more of an issue when the sensor is non-collocated with the actuator. We illustrate that adaptive control can stabilize otherwise unstable dynamics due to the presence of unmodelled dynamics. Third, transient responses of the position of the isolation system are significantly influenced by a high-gain acceleration controller when it includes integral action. An important aspect of the g-LIMIT is the accelerometer bias and the deviation of the platform it causes as a result of integral control. By employing adaptive neural networks for both the inner-loop and outer-loop controllers, we illustrate that adaptive control can improve both steady-state responses and transient responses in position. A feature in the design is that high-band pass and low pass filters are applied to the error signal used to adapt the weights in the neural network and the adaptive signals, so that the adaptive processes operate over targeted ranges of frequency. This prevents the inner and outer loop adaptive processes from interfering with each other.
-
ItemFault tolerant nonlinear adaptive flight control(Georgia Institute of Technology, 2003-04-01) Calise, Anthony J. ; Craig, James I.
-
ItemASOP-affordable system optimization process(Georgia Institute of Technology, 1995) Craig, James I.
-
ItemStructural behavior of precast cladding and connections phase I(Georgia Institute of Technology, 1985) Goodno, Barry J. ; Craig, James I.
-
ItemDevelopment of a solar radiation model for Shenandoah(Georgia Institute of Technology, 1981) Craig, James I.
-
ItemInfluence of nonstructural cladding on dynamic properties and response of highrise buildings(Georgia Institute of Technology, 1980) Goodno, Barry J. ; Craig, James I.
-
ItemMonitoring the Shenandoah (Georgia) Community Recreation Center solar cooling, heating and hot water system(Georgia Institute of Technology, 1979) Craig, James I. ; Jeter, Sheldon M.
-
ItemPreliminary design (Phase III) of a solar total energy-large scale experiment, Fort Hood(Georgia Institute of Technology, 1978) Williams, James Richard ; Bomar, S. H. ; Craig, James I.