Shahab Torkamani

Observer-based delayed feedback attitude control for single- and multi-actuator maneuvers

Observer-based attitude controllers for single- and multi-actuator maneuvers are developed from the delayed state feedback control laws obtained by the Lyapunov-Krasovskii functional and inverse dynamics approaches, respectively. The TRIAD algorithm is employed to process the observations. The observer gain is selected based on the extended Kalman-Bucy (EKB) filter, and a novel delay estimation approach is used to provide the estimates of the delay. The observer-based delayed feedback control laws are shown to be capable of accurate control of spacecraft attitude from noise-corrupted attitude measurements.

Damage Assessment Using Hyperchaotic Excitation and State-Space Geometry Changes

The current study explores the use of a steady-state hyperchaotic signal to probe a system for state-space geometry changes used for structural health monitoring applications. This is an extension of a previous chaotic interrogation technique approach that exploited the intrinsic high sensitivity of chaotic systems to subtle changes of the parameters. The enhanced technique proposed in this paper explores a novel structural excitation, namely a hyperchaotic excitation, which exhibits a chaotic behavior wherein at least two Lyapunov exponents are positive due to stretching of the phase space in multiple directions. A feature called average local attractor variance ratio (ALAVR), which is based on attractor geometry, is used to compare the geometry of a baseline attractor to a test attractor. The enhanced technique is applied to analytically and experimentally analyze the response of an 8-degree-of-freedom system to the hyperchaotic excitation for the sake of damage assessment. A comparison between the results obtained from current hyperchaotic excitation vs. a chaotic excitation highlights the higher sensitivity of the hyperchaotic excitation. Thus, hyperchaotic interrogation can be used as an alternative damage assessment technique when increased sensitivity to small amounts of damage is required.Copyright

Real-Time Damage Identification in Nonlinear Smart Structures Using Hyperchaotic Excitation and Stochastic Estimation

Among numerous damage identification techniques, those which are used for online data-driven damage identification have received considerable attention recently. One of the most widely-used vibration-based time-domain techniques for nonlinear system identification is the extended Kalman filter, which exhibits a good performance when the parameter to be identified is a constant parameter. However, it is not as successful in identification of changes in time-varying system parameters, which is essential for real-time identification. Alternatively, the extended Kalman-Bucy filter has been recently proposed due to its enhanced capabilities in parameter estimation compared with extended Kalman filter. On the other hand, when applied as the excitation in some attractor-based damage identification techniques, chaotic and hyperchaotic dynamics produce better outcomes than does common stochastic white noise. The current study combines hyperchaotic excitations and the enhanced capabilities of extended Kalman-Bucy filter to propose a real-time approach for identification of damage in nonlinear structures. Simulation results show that the proposed approach is capable of online identification and assessment of damage in nonlinear elastic and hysteretic structures with single or multiple degrees-of-freedom using noise-corrupted measured acceleration response.