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- W2248093417 abstract "This paper presents a new H∞ optimal control approach for active noise blocking (ANB), based on a disturbance learning observer (DLO). The proposed method is robust, and capable of attenuationg all destabilizing disturbances affecting the ANB system, gradually. In addition, the proposed technique is given in a nonminimal state space realization (NSSR) scheme, that allows one to generate an equivalent set of states for ANB system, using measured inputs and outputs, without differentation, despite perturbations and uncertainties in the system model that result from system identification, nonlinearities, and drifting of system properties. Actual hardware experiments using a DSP have been carried out in order to verify the applicability and the performance of the proposed method for vibration control of a panel for active noise blocking purposes in a 3D acoustic enclosure." @default.
- W2248093417 created "2016-06-24" @default.
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- W2248093417 date "2008-10-01" @default.
- W2248093417 modified "2023-09-26" @default.
- W2248093417 title "Disturbance Learning Robust H∞ Active Noise Blocking" @default.
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