摘要
建立了一种发动机-汽车振动模型,利用神经网络自适应主动振动控制与机械被动控制相结合的方法,通过自适应控制算法,在控制过程中自动调整、修改和完善控制参数,从而达到了最佳的控制效果。应用MATLAB语言编程仿真表明:设计的神经网络自适应控制系统的振动控制效果优于机械被动隔振和半主动隔振(PID与模糊控制),而且对振动环境的自适应能力强,有很强的鲁棒性和很好的减振效果。
This paper established a vibration model of an ICE-vehicle. Neural network adaptive active vibration control techniques and mechanical passive vibration isolating methods were combined to get the control parameters modified and consummated automatically using adaptive control algorithm, and achieved optimal results eventually. It＇s verified by emulating using MATLAB language that the designed control system is more effective than both passive mechanical vibration isolation and semi-active vibration isolation （PID and fuzzy control）, it has relatively higher adaptive abilities to environments, stronger robot properties and better vibration reducing effects.
出处
《内燃机工程》
EI
CAS
CSCD
北大核心
2006年第1期71-75,共5页
Chinese Internal Combustion Engine Engineering
关键词
内燃机
神经网络
自适应控制
模糊控制
主动振动控制
仿真
I. C. Engine
Neural Network
Adaptive Control
Fuzzy Control
Vibration Active Control
Simulation
