While positive feedback exists in an active vibration control system, it may cause instability of the whole system. To solve this problem, a feedforward adaptive controller is proposed based on the Fihered-U recursive...While positive feedback exists in an active vibration control system, it may cause instability of the whole system. To solve this problem, a feedforward adaptive controller is proposed based on the Fihered-U recursive least square （FURLS） algorithm. Algorithm development process is presented in this paper. Real time active vibration control experimental tests were done. The experiment resuits show that the active control algorithm proposed in this paper has good control performance for both narrow band disturbances and broad band disturbances.展开更多
A multi-channel active vibration controller based on a filtered-u least mean square （FULMS） control algorithm is analyzed and implemented to solve the problem that the vibration feedback may affect the measuring of ...A multi-channel active vibration controller based on a filtered-u least mean square （FULMS） control algorithm is analyzed and implemented to solve the problem that the vibration feedback may affect the measuring of the reference signal of the filtered-x least mean square （FXLMS） algorithm in the field of active vibration control. By analyzing the multi-channel FULMS algorithm, the multi-channel controller structure diagram is given, while by analyzing multi-channel FXLMS algorithm and its algorithmic procedure, the control channel model identification strategy is given. This paper also provides an easy but practical way to configure the actuators based on the maximal modal force rule. Taking the configured piezoelectric beam as the research object, an active vibration control experimental platform is established to verify the effectiveness of the identification strategy as well as the FULMS control scheme. Simulation and actual control experiments are done after the model parameters are obtained. Both the simulation and actual experiment results show that the designed multi-channel vibration controller has a good control performance with low order model and rapid convergence.展开更多
基金Supported by the National Natural Science Foundation of China(No.90716027,51175319)
文摘While positive feedback exists in an active vibration control system, it may cause instability of the whole system. To solve this problem, a feedforward adaptive controller is proposed based on the Fihered-U recursive least square （FURLS） algorithm. Algorithm development process is presented in this paper. Real time active vibration control experimental tests were done. The experiment resuits show that the active control algorithm proposed in this paper has good control performance for both narrow band disturbances and broad band disturbances.
基金Supported by the National Natural Science Foundation of China （No. 90716027, 51175319）, and Shanghai Talent Development Fund （No.2009020）.
文摘A multi-channel active vibration controller based on a filtered-u least mean square （FULMS） control algorithm is analyzed and implemented to solve the problem that the vibration feedback may affect the measuring of the reference signal of the filtered-x least mean square （FXLMS） algorithm in the field of active vibration control. By analyzing the multi-channel FULMS algorithm, the multi-channel controller structure diagram is given, while by analyzing multi-channel FXLMS algorithm and its algorithmic procedure, the control channel model identification strategy is given. This paper also provides an easy but practical way to configure the actuators based on the maximal modal force rule. Taking the configured piezoelectric beam as the research object, an active vibration control experimental platform is established to verify the effectiveness of the identification strategy as well as the FULMS control scheme. Simulation and actual control experiments are done after the model parameters are obtained. Both the simulation and actual experiment results show that the designed multi-channel vibration controller has a good control performance with low order model and rapid convergence.
