Past and Current Research


Robust Parametric Control Applications to Space Structures
Recent developments in robust parametric control are being studied for their application to the problem of position control and vibration control of a space platform including LAN-7 satellite, flexible slewing beam, and large space structures.
This research is funded by NASA Headquarters.

Fault and Damage Detection
Structural fault/damage detection research consists of trying to detect and isolate, if possible, fault/damage from the structures so that the structures can perform normal operation. The methodologies investigating here are based on the observation of behavioral changes of the structures. These changes may be effectively monitored by detecting whether the responses of the structures are within a predetermined response set which is described in terms of a transfer function family.
This research is funded by NASA Headquarters.

Robotic Telescope Scheduling Problem
The Center operates four remote telescopes, they are the VU/TSU 16 inch, TSU/ASO 32 inch, SAO/TSU 30 inch, and Fairborn 10 inch telescopes. Two more telescopes, the AST 2 meter and AIT 24 inch, are currently under construction. All of these are robotic telescopes which are remotely controlled from the Center located in Nashville, Tennessee. In order to achieve better utilization of telescopes' time, we are currently developing a new state-of-art optimal scheduling mechanism which will eventually replace the scheduler our astronomers are presently using.
This research is funded by NASA Ames Research Center.

Low Order and Parametrically Less Sensitive Controller Design
It is found that controllers that robustly stabilize a plant against plant uncertainty are usually high order and extremely sensitive with respect to controller parameter perturbations. To overcome this problem, the research aims to develop new control design methodologies that can result a low order controller which tolerates some degree of controller perturbations.

Structural Damage Detection
The operation of structures such as spacecraft, aircraft, ground vehicles, and weapons systems is sensitive to damage in the structural components. To maintain the performance and safe operation of the systems, one must monitor the mechanical health of the structures. Recently we have developed an approach for damage detection of structures by using only a few sensors. The research is to develop an effective and inexpensive technology to detect structural damage.
This research is funded by NASA Headquarters.

System Identification for Robust Control Design
Modeling a dynamic system with uncertainties and parametric changes is an important and challenging task for researchers in system identification and robust control communities. Recently we have developed an approach that can precisely quantify model uncertainty via the intervals of transfer function coefficients. The research is to develop an effective tool to model a dynamic system with uncertainty directly from experimental data for robust control design.
This research is funded by NASA Headquarters.

Machinery Monitoring and Diagnostics
Machinery condition monitoring and fault diagnosis are crucial for effective maintenance in industry.

Large-Scale Control and Distributed Parameter Systems Under Stochastic Structural perturbations
Large-scale hereditary/non-hereditary control and distributed systems under stochastic structural perturbations is being studied.Three principal areas of research, namely, (i) qualitative properties(Stability, convergence, etc.), (ii) error estimation, and (iii) applications in biological, chemical and engineering sciences are emphasized.
This research is funded by Army Research Office .

Stable Robust Adaptive Control Using Neural Networks
The development of stable adaptive algorithms for the control of a class of nonlinear interval plants using neural networks.
Funded by Center of Excellence in Information Systems at Tennessee State University.

Vibration Attenuation Using Space Realizable Actuators
The development of a stable adaptive neural network controller to dampen the vibrations of a space structure using a reciprocating mass actuator.
Funded by Center of Excellence in Information Systems at Tennessee State University.

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