The actuator and sensor placement problem for active vibration control of large cable net structures is investigated in this paper.Since the structures exhibit closely spaced modes in the range of low frequencies,the ...The actuator and sensor placement problem for active vibration control of large cable net structures is investigated in this paper.Since the structures exhibit closely spaced modes in the range of low frequencies,the number of modes to be considered is quite large after modal truncation,while only a limited number of actuators and sensors are to be placed.This makes it hard to determine the actuator and sensor locations with the existing placement methods in the literature such as the methods based on the controllability/observability grammian.To deal with this issue,an actuator and sensor placement method based on singular value decompositions(SVD)of the input and output matrices is proposed,which guarantees the modal controllability and observability of the system.The effectiveness of the SVD based method is verified through numerical simulations in which comparisons are conducted between randomly-chosen locations and the optimal ones obtained by a genetic algorithm.展开更多
基金National Natural Science Foundation of China(11290153)。
文摘The actuator and sensor placement problem for active vibration control of large cable net structures is investigated in this paper.Since the structures exhibit closely spaced modes in the range of low frequencies,the number of modes to be considered is quite large after modal truncation,while only a limited number of actuators and sensors are to be placed.This makes it hard to determine the actuator and sensor locations with the existing placement methods in the literature such as the methods based on the controllability/observability grammian.To deal with this issue,an actuator and sensor placement method based on singular value decompositions(SVD)of the input and output matrices is proposed,which guarantees the modal controllability and observability of the system.The effectiveness of the SVD based method is verified through numerical simulations in which comparisons are conducted between randomly-chosen locations and the optimal ones obtained by a genetic algorithm.
