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Performance and power consumption of a decentralized velocity feedback control system with six inertial mass actuators on a laboratory truss structure

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This paper presents numerical studies and preliminary experimental results on a decentralized velocity feedback active vibration control (AVC) system. The system is composed of six inertial mass actuators (IMAs) installed on a truss structure. The performance and power consumption of the AVC system are analysed and compared for different actuator placements and gain settings. The actuator placements are derived using a controllability performance index (PI), calculated using a reduced order state space representation of the truss structure. The PI is first evaluated for each of fourteen selected input/output ports, and then for all possible placement combinations of the six IMAs on the fourteen ports. The IMA placements with the highest and the lowest PI are considered for further studies. The stability of the feedback loops is first studied individually for each actuator position using the open-loop frequency response functions (OL FRFs). The individual gains that provide a 6 dB stability gain margin and those that limit the control spillover to a maximum of 6 dB are evaluated. The stability of the system with six decentralized feedback loops for the two chosen actuator placements is then studied using the generalized Nyquist criterion. The performance and the power consumption of the AVC system are then analysed numerically and experimentally for three different gain settings: a) set to the individual 6 dB spillover gains; b) scaled in order to obtain the 6 dB spillover requirements in the generalized Nyquist; and c) set to one uniform value. The results of this study aim to help choosing optimal energy efficient actuator placements and gain settings for decentralized velocity feedback AVC systems on arbitrary structures. The results of initial experimental studies on a laboratory truss structure are also presented and discussed.

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Document Type: Research Article

Affiliations: Fraunhofer LBF, Germany

Publication date: 07 December 2017

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