REAL-TIME SUBSPACE IDENTIFICATION AND OPTIMAL CONTROL FOR ACTIVE NOISE CANCELLATION

摘要

In this paper, a combination of a novel recursive subspace identification and receding horizon optimal control is developed for real-time implementation, via a digital signal processor (DSP), using only input-output measurements. The proposed recursive strategy can be parameterized in terms of recursive approximation of subspace intersections and adaptive estimation of state sequences. The proposed integrated modeling-control strategy can be implemented, in real time, with minimum knowledge of the controlled system. Actual hardware experiments on feedback active noise control problem in a duct have been carried out in order to verify the performance of the proposed methodology.