摘要
在飞行器稳定性控制问题的研究中,针对含有外部扰动、参数不确定性、状态和控制时滞的非线性飞行器系统,提出了一种时滞状态反馈控制与神经网络自适应估计相结合的方法。对非线性系统线性化处理得到飞行器线性模型,并由线性矩阵不等式(LMI)设计反馈控制律;采用径向基函数(RBF)神经网络自适应在线估计策略,对反馈控制律进行补偿以消除未知非线性影响;采用Lyapunov稳定性理论证明了在所设计控制律作用下,闭环系统渐近稳定同时满足H"性能指标。仿真结果验证了上述方法的可行性及有效性。
One control method was proposed in this paper, aiming at the control law design of nonlinear vehicle system with external disturbance, parameter uncertainty, state delay and control delay. The method is based on time -delay state feedback controller and neural network adaptive estimation. The linear model was obtained by lineariza- tion of the nonlinear vehicle system and the feedback control law was designed by Linear Matrix Inequality （LMI）. The effect of unknown nonlinearity of the control law was compensated by adaptive online estimation strategy, which is based on radial basis function （RBF） neural network. It has been proved by Lyapunov theory that the close-loop sys- tem is asymptotic stable and has the H~ performance under the designed control law. The feasibility and effectiveness of the method were also verified by simulations.
出处
《计算机仿真》
CSCD
北大核心
2013年第5期77-81,共5页
Computer Simulation
基金
航空科学基金(20111396011)
关键词
非线性飞行器系统
时滞控制
神经网络
自适应估计
Nonlinear vehicle system
Time-delay control
Neural network
Adaptively estimate
作者简介
涂再云（1987-），男（汉族），湖北咸宁人，硕士研究生，主要研究领域为：智能控制；
陆阿坤（1955-），男（汉族），浙江湖州人，教授，硕士研究生导师，主要研究领域为：智能故障诊断；
杜军（1973-），男（汉族），山西太原人，副教授，士研究生导师，主要研究领域为：智能故障诊断。
