In traditional system designs for feedback structural control systems, the structure is assumed to be linear time invariant (LTI). However, extreme load events on the structure can damage the structure leading to violation of the time invariance assumption. This study proposes an online adaptive control strategy that tracks the time varying characteristics of a structural system with the optimal control law recursively derived for the system. Continuous system identification executed concurrently with derivation of optimal control laws is possible using the low-power, dual-core Martlet wireless node developed at the University of Michigan. The wireless platform executes online system identification recursively on one processor pipeline while a control law based on linear quadratic regulation (LQR) is derived and implemented concurrently on the second pipeline. By parallelizing the implementation of the LQR control law and system identification algorithm, the wireless sensing network is shown to be capable of learning and adapting to system changes in real-time. Simulation and experiments on a 4 story benchmark shear structure is utilized to show the validity and scalability of the proposed adaptive feedback control approach.
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