o[Characterization and Mitigation of Failures in Complex Dynamical Systems (MURI2001)]o
o[Intelligent Supervisory Control of Tactical Operations with Unmanned Vehicles]o
o[Real-time Life Extending Control of Mechanical and Aerospace Systems]o
o[Real-time Non-Destructive Evaluation of Fatigue Crack Damage]o

Characterization and Mitigation of Failures in Complex Dynamical Systems

The Multidisciplinary University Research Initiative (MURI) project provides a scientific basis for engineering dependability in tactical operations involving human-operated machineries and unmanned vehicles.  It envisions a fundamentally new approach to engineering and operation of complex informational systems for pervasive fault tolerance.  Instead of specifying parameters for worst-case design of components, we postulate designing these systems by specifying a scalable set of resources (components) that interact to support evolving operational needs of multiple defense and commercial applications in uncertain dynamical environments.  Dependability of operations is achieved by identifying and mitigating the origins of disorder through dynamic coordination and control of available system resources.

For theoretical analyses, we model complex dynamical systems as hybrid interacting automata whose continuously varying dynamics capture the physical process at the lowest level of abstraction.  Discrete event models at the higher levels capture the cognitive response of the system to observed emerging physical phenomena.  We have used this concept to utilize the dynamic structural behaviors of materials in formulating damage mitigating control algorithms at the system level to enhance the life of critical mechanical components.  The goal is to formulate analytical models of the higher level dynamics of component interactions triggered by various types of failures to (i) predict emerging pathological system behavior from time-series observations of events and their dynamic interactions, and (ii) formulate adaptive mechanisms to circumvent or mitigate the effects of pathological behavior.

New and significant theoretical results will be experimentally validated at the Smart Machines Collaboratory.  The Collaboratory will emulate observed pathological patterns through scientifically designed realistic, medium complexity simulation experiments.  High-fidelity physics based models of components, hardware-in-the-loop, and experimental data will be generated and maintained at the Failure Simulation Network facility that is a part of the Collaboratory.  The graduate students, faculty, and other research personnel will have the opportunity to collaborate with industry and Government laboratories.  The research projects in this area are sponsored by:

         U.S. Army Research Office (ARO)
         NASA Glenn Research Center (GRC)
         NASA Langley Research Center (LaRC)

Further details of the project are available at

Details of  Networked Robotics and Sensor Intelligence (NRSI) Laboratory are available at


Intelligent Supervisory Control of Tactical Operations with Unmanned Vehicles

The main objective of the research is to attain agile and stable control of distributed tactical operations with unmanned airborne, land-borne, and ocean-borne vehicles.  The operating environment is uncertain and rapidly changing…The goal is to develop: (i) theoretical techniques and tools to provide decision support for Command, Control, and Communications (C3) operations;  (ii) a flexible modeling framework to support management of the dynamics in a C3 environment; (iii) new concepts and architectures to spawn revolution in C3 technologies for both military and commercial applications; and (iv)  a versatile testbed and prototype components for validation of C3  concepts and architectures.  This research project is sponsored by:

U.S. Defense Advanced Research Projects Agency (DARPA)
U.S. Office of Naval Research (ONR)
Real-time Life Extending Control of Mechanical and Aerospace Systems

The main objective of the research is to achieve high performance of operating machinery with increased reliability, availability, component durability, and maintainability.  The goal of Life Extending Control is to ensure structural integrity of mechanical components by minimizing the material damage (e.g., fatigue cracking) while simultaneously maximizing the system dynamic performance via active control.  This requires interdisciplinary efforts involving Systems Sciences and Mechanics of Materials for augmentation of the current system-theoretic and artificial intelligence (AI) techniques for synthesis of decision and control laws with governing equations and inequality constraints that would model the properties of the materials for the purpose of damage representation and failure prognosis.  The major challenge in these research projects is to characterize the damage generation process in a continuous-time setting, and then utilize this information for synthesizing algorithms of robust control, diagnostics, and risk assessment.   The research projects also involve the following areas:

Robust Control of Dynamical Processes (e.g., Aircraft, Rocket Engines, and Energy Systems);
Information-based Maintenance and Prognostics of Machinery Components;
Stochastic Modeling of Fatigue Crack Growth in Structural Materials.
The laboratories for life extending Control are equipped with advanced material testing devices, computer-controlled microscopes, and electronic and acoustic instruments for non-destructive testing.  The basic concepts of life extending control and the pertinent results have been reported in a number of recent publications citing examples of applications to reusable rocket engines and fossil-fueled power plants.  The research projects in this area are sponsored by:
Electric Power Research Institute (EPRI)
National Academy of Sciences (NAS)
National Science Foundation (NSF)
NASA Glenn Research Center (GRC)
NASA Langley Research Center (LaRC)

Real-time Non-Destructive Evaluation of Fatigue Crack Damage

The goal of the proposed research is to develop real-time non-destructive evaluation (NDE) methods for health monitoring and residual life prediction of airframe structures in both aging and new aircraft.  The specific objectives are: (i0 quantification and estimation of fatigue crack damage; and (ii) assessment of the time to onset of widespread fatigue damage.  The technical approach relies on fusion of heterogeneous information derived from physics-based state-space (i.e., described by difference or differential equations) models of fatigue crack damage and real-time sensor data.  The analytical part of the research requires model development and formulation of filter algorithms for on-line estimation and prediction of damage states.  The analytical research will be supported by laboratory experimentation on a special-purpose fatigue test apparatus that is equipped with multiple sensing devices — electromagnetic, mechanical, optical, and ultrasonic.  Fusion of multiple sensor data with the stochastic state-space model of fatigue crack damage will allow non-destructive evaluation of the current state of damage and prediction of the residual life in real time.  This hardware-software combination constitutes a novel NDE system that can be executed on inexpensive platforms such as a Pentium processor for adaptation to commercial fixed-wing transport aircraft, rotorcraft, and general aviation aircraft.  As such this NDE system is suited for sensing and real-time monitoring of fatigue crack damage for mitigation of failures of flight-critical sub-systems and components during normal operations as well as for controlled flight into terrain (CFIT) conditions. This research project is sponsored by:

ARINC Corporation
National Science Foundation (NSF)
NASA Langley Research Center (LaRC)

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