摘要
提出了一种改进的自适应模糊滑模大包线飞行控制方法。该方法以经模拟退火粒子群算法优化的小波神经网络实现非线性模型的逆,能够更加细致地逼近非线性模型,并针对自适应控制的鲁棒性与瞬态性能差的缺点,将滑模控制与自适应控制相结合共同补偿逆误差,提高了自适应控制的鲁棒性与瞬态性。仿真结果表明:所设计的自适应模糊滑模大包线飞行控制器具有优良的控制性能。
An improved adaptive fuzzy sliding mode large envelope flight control method was approved. The method realized the inversion of the nonlinear model using wavelet neural network. In order to approach the nonlinear model accurately, the wavelet neural network was optimized using simulated annealing particle swarm optimization algorithm. The sliding mode control was used to compensate the inversion error with adaptive control for improving robustness and transient characteristic performance. The simulation results show the design adaptive fuzzy sliding mode large envelope flight controller has excellent control performance.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2008年第5期1262-1264,1278,共4页
Journal of System Simulation
关键词
非线性控制
自适应控制
小波神经网络
滑模控制
模拟退火
nonlinear control
adaptive control
wavelet neural network
sliding mode control
simulated annealing
