In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural...In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural network proportion-integration-differentiation （PID） control parameters on-line adjustment is utilized to improve system accuracy, celerity and stability. Simulation results indicate that with the control system proposed in this paper, the system deviation is reduced, therefore accuracy is improved; response speed for step signal and sinusoidal signal gets faster, thus acceleration is rapidly improved; and the system can be restored to the control value in case of interfering, so stability is improved.展开更多
In order to improve the yaw stability of the vehicle with active front steering system, an adaptive PID-type fuzzy control scheme is designed to make the yaw rate tracking the desired values as close as possible. A 2-...In order to improve the yaw stability of the vehicle with active front steering system, an adaptive PID-type fuzzy control scheme is designed to make the yaw rate tracking the desired values as close as possible. A 2-DOF vehicle model with active front steering is built firstly, and then the fuzzy PID controller is designed in detail. The simulation investigations of the yaw stability with different steering ma- neuvers are performed. The simulation results show the effectiveness of the fuzzy PID controller for improving the vehicle＇s yaw stability.展开更多
文摘In order to design an effective hydraulic motor speed control system, Matlab_Simiulink and AMESim co-simulation technology is adopted to establish more accurate model and reflect the actual system. The neural network proportion-integration-differentiation （PID） control parameters on-line adjustment is utilized to improve system accuracy, celerity and stability. Simulation results indicate that with the control system proposed in this paper, the system deviation is reduced, therefore accuracy is improved; response speed for step signal and sinusoidal signal gets faster, thus acceleration is rapidly improved; and the system can be restored to the control value in case of interfering, so stability is improved.
基金Supported by the National Natural Science Foundation of China （No.50705008）
文摘In order to improve the yaw stability of the vehicle with active front steering system, an adaptive PID-type fuzzy control scheme is designed to make the yaw rate tracking the desired values as close as possible. A 2-DOF vehicle model with active front steering is built firstly, and then the fuzzy PID controller is designed in detail. The simulation investigations of the yaw stability with different steering ma- neuvers are performed. The simulation results show the effectiveness of the fuzzy PID controller for improving the vehicle＇s yaw stability.
