With the revival of magnetorheological technology research in the 1980’s, its application in vehicles is in- creasingly focused on vibration suppression. Based on the importance of magnetorheological damper modeling,...With the revival of magnetorheological technology research in the 1980’s, its application in vehicles is in- creasingly focused on vibration suppression. Based on the importance of magnetorheological damper modeling, non- parametric modeling with neural network, which is a promising development in semi-active online control of vehicles with MR suspension, has been carried out in this study. A two layer neural network with 7 neurons in a hidden layer and 3 inputs and 1 output was established to simulate the behavior of MR damper at different excitation currents. In the neural network modeling, the damping force is a function of displacement, velocity and the applied current. A MR damper for vehicles is fabricated and tested by MTS; the data acquired are utilized for neural network training and vali- dation. The application and validation show that the predicted forces of the neural network match well with the forces tested with a small variance, which demonstrates the effectiveness and precision of neural network modeling.展开更多
The research on the form and control method of impact load arresting buffer has been an active topic in the field of buffer arresting system(BAS).It becomes significant on reducing the weight of arresting system,impro...The research on the form and control method of impact load arresting buffer has been an active topic in the field of buffer arresting system(BAS).It becomes significant on reducing the weight of arresting system,improving the hindered efficiency,and guaranteeing the security of BAS.The hydraulic hindered device of impact load is currently used in BAS.There are some problems.For example,the system needs large power sources.However,once the power of active hydraulic control system is turned off,there arise unpredictable security risks.An arresting form of semi-active control based on magneto-rheological damper(MRD) is proposed,and the mechanical model of the BAS is established.Meanwhile,the state equation of impact load BAS is established according to the characteristics of impact load buffer arresting,and its sliding model buffer control is achieved.Due to the chattering characteristic of the output signal of sliding mode controller,the method to prevent chattering is designed based on short-term energy and zero-crossing rate detection.For the model and chattering suppression of sliding model buffer control algorithms,simulation results show that the proposed state equation and the arresting model are reasonable,and the design of semi-active control algorithm is effective.On the condition of the buffer control system requirement and the accuracy,the proposed algorithms effectively control the chattering of sliding mode control algorithms,and improve the security of the BAS.展开更多
基金Projects 50135030 and 60404014 supported by National Natural Science Foundation of China
文摘With the revival of magnetorheological technology research in the 1980’s, its application in vehicles is in- creasingly focused on vibration suppression. Based on the importance of magnetorheological damper modeling, non- parametric modeling with neural network, which is a promising development in semi-active online control of vehicles with MR suspension, has been carried out in this study. A two layer neural network with 7 neurons in a hidden layer and 3 inputs and 1 output was established to simulate the behavior of MR damper at different excitation currents. In the neural network modeling, the damping force is a function of displacement, velocity and the applied current. A MR damper for vehicles is fabricated and tested by MTS; the data acquired are utilized for neural network training and vali- dation. The application and validation show that the predicted forces of the neural network match well with the forces tested with a small variance, which demonstrates the effectiveness and precision of neural network modeling.
基金the National Natural Science Foundation of China(Nos.61074090 and 60804025)the Innovation Funds of Aviation Industry Corporation of China(No.cxy2013SH16)the Natural Science Foundation of Liaoning(Nos.2015020061 and 2015020069)
文摘The research on the form and control method of impact load arresting buffer has been an active topic in the field of buffer arresting system(BAS).It becomes significant on reducing the weight of arresting system,improving the hindered efficiency,and guaranteeing the security of BAS.The hydraulic hindered device of impact load is currently used in BAS.There are some problems.For example,the system needs large power sources.However,once the power of active hydraulic control system is turned off,there arise unpredictable security risks.An arresting form of semi-active control based on magneto-rheological damper(MRD) is proposed,and the mechanical model of the BAS is established.Meanwhile,the state equation of impact load BAS is established according to the characteristics of impact load buffer arresting,and its sliding model buffer control is achieved.Due to the chattering characteristic of the output signal of sliding mode controller,the method to prevent chattering is designed based on short-term energy and zero-crossing rate detection.For the model and chattering suppression of sliding model buffer control algorithms,simulation results show that the proposed state equation and the arresting model are reasonable,and the design of semi-active control algorithm is effective.On the condition of the buffer control system requirement and the accuracy,the proposed algorithms effectively control the chattering of sliding mode control algorithms,and improve the security of the BAS.
