Modeling and robust control of smart structures

The design and implementation of control strategies for large, flexible smart structures presents challenging problems. One of the difficulties arises in the approximation of high-order finite element models with low order models. Another difficulty in controller design arises from the presence of unmodeled dynamics and incorrect knowledge of the structural parameters. In this paper, the balance-truncation reduced-order models are employed in deriving lower-order models for complex smart structures. These methods do not introduce any spill-over problems in the closed-loop response of the system. The simplified analytical models are compared with models developed by structural identification techniques based on vibration test data. To minimize the effects of uncertainties on the closed-loop system performance of smart structures, robust control methodologies have been employed in the design of controllers. The reduced order models are employed in the design of robust controllers. To demonstrate the capabilities of shape-memory-alloy actuators, we have designed and fabricated a three-mass test article with multiple shape-memory-alloy (NiTiNOL) actuators. Generally, the non-collocation of actuators and sensors presents difficulties in the design of controllers. Controllers for a test article with non-collocated sensors and actuators are designed, implemented and tests. The closed-loop system response of the test article with two actuators and sensors has been experimentally determined and presented in the paper.