Intelligent Control of Mechanical Structures for Damage Mitigation and Failure Prognosis

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Interdisciplinary research in the fields of control systems, structural dynamics, and materials science is proposed for damage mitigation and failure prognosis of mechanical structures as an augmentation to intelligent control and diagnostics in complex dynamic processes. The key ideas of the proposed research are (i) a significant improvement in service life could be achieved by a small reduction in the system dynamic performance; and (ii) impending failures of critical plant components can be predicted in real time. Specifically, prognoses of impending component failures are critical for enhancement of plant and personnel safety, improvement of availability and operability, and reduction of operational cost. As the science and technology of materials continue to evolve, the design methodologies for damage- mitigating control and failure prognostics must have the capability of easily incorporating an appropriate representation of material properties. This requires augmentation of the current system-theoretic and AI-based 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 this research is to extract the information from the material properties and then utilize this information in a mathematical form for synthesizing intelligent control and diagnostic systems.