The LQG control system is employed as vehicle suspension's optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal perform...The LQG control system is employed as vehicle suspension's optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal performances when the suspension parameters change, a model reference adaptive fuzzy control (MRAFC) strategy is presented. The LQG control system serves as the reference model in the MRAFC system. The simulation results indicate that the presented MRAFC system can adapt to the parameters variation of vehicle suspension and track the optimality of the LQG control system, the presented vehicle suspension MRAFC system has the ability to adapt to road conditions and suspension parameters change.展开更多
The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is des...The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is designed, in which the sus pension travel output of the adaptive LQG control system is taken as the tracking objective. The simulation results prove that the suspension travel and vertical acceleration can be tracked simultaneously with the simple fuzzy controller, and the tracking effect of fuzzy control is better than that of the PID controller.展开更多
The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative ...The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative are used as the inputs of the fuzzy logic controller, and the fuzzy logic controller output determines the semi-active suspension controllable damping force. The fuzzy logic controller is to minimize the mean square root of acceleration of the driver's seat. The control forces of controllable dampers behind the first road wheel are obtained by time delay, and the delay times are determined by the vehicle speed and axles distances. The simulation results show that this control method can decrease the acceleration of driver's seat and the suspension travel of the first road wheel, the ride quality is improved obviously.展开更多
On the basis of analyzing the system constitution of vehicle semi-active suspension, a 4-DOF (degree of freedom) dynamic model is established. A tunable fuzzy logic controller is designed by using without quantificati...On the basis of analyzing the system constitution of vehicle semi-active suspension, a 4-DOF (degree of freedom) dynamic model is established. A tunable fuzzy logic controller is designed by using without quantification method and taking into account the uncertainty, nonlinearity and complexity of parameters for a vehicle suspension system. Simulation to test the performance of this controller is performed under random excitations and definite disturbances of a C grade road, and the effects of time delay and changes of system parameters on the vehicle suspension system are researched. The numerical simulation shows that the performance of the designed tunable fuzzy logic controller is effective, stable and reliable.展开更多
文摘The LQG control system is employed as vehicle suspension's optimal target system, which has an adaptive ability to the road conditions and vehicle speed in a limited bandwidth. In order to keep the optimal performances when the suspension parameters change, a model reference adaptive fuzzy control (MRAFC) strategy is presented. The LQG control system serves as the reference model in the MRAFC system. The simulation results indicate that the presented MRAFC system can adapt to the parameters variation of vehicle suspension and track the optimality of the LQG control system, the presented vehicle suspension MRAFC system has the ability to adapt to road conditions and suspension parameters change.
基金Sponsored by Ministerial Level Equipment Pre-research Foundation(623010202 .4)
文摘The control strategy of the model travel tracking for the vehicle suspension sys tem is presented based on analyzing the responses of the vehicle suspension tra vel. A fuzzy control system of vehicle suspension is designed, in which the sus pension travel output of the adaptive LQG control system is taken as the tracking objective. The simulation results prove that the suspension travel and vertical acceleration can be tracked simultaneously with the simple fuzzy controller, and the tracking effect of fuzzy control is better than that of the PID controller.
文摘The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative are used as the inputs of the fuzzy logic controller, and the fuzzy logic controller output determines the semi-active suspension controllable damping force. The fuzzy logic controller is to minimize the mean square root of acceleration of the driver's seat. The control forces of controllable dampers behind the first road wheel are obtained by time delay, and the delay times are determined by the vehicle speed and axles distances. The simulation results show that this control method can decrease the acceleration of driver's seat and the suspension travel of the first road wheel, the ride quality is improved obviously.
基金Funded by the National Natural Science Foundation of China (NO.50135030)
文摘On the basis of analyzing the system constitution of vehicle semi-active suspension, a 4-DOF (degree of freedom) dynamic model is established. A tunable fuzzy logic controller is designed by using without quantification method and taking into account the uncertainty, nonlinearity and complexity of parameters for a vehicle suspension system. Simulation to test the performance of this controller is performed under random excitations and definite disturbances of a C grade road, and the effects of time delay and changes of system parameters on the vehicle suspension system are researched. The numerical simulation shows that the performance of the designed tunable fuzzy logic controller is effective, stable and reliable.
