神经网络在质量矩导弹控制系统上的应用

以所建立的质量矩导弹数学模型为基础,通过对模型合理的简化,得到一个耦合的非线性动力学系统,由于存在参数的不确定性以及建模误差,考虑到质量矩导弹的鲁棒性要求,采用神经网络自适应控制器对系统进行补偿。通过李亚普诺夫稳定理论证明跟踪误差是指数收敛的,仿真结果验证了这种方法的有效性。

Using of neural networks for the missile control system with moving masses

Based on the constructed model of moving mass control for missile, presents a coupled nonlinear dynamic system by rational simplifying.With the request of robustness of the system for the presence of uncertainty of parameters and errors of model ,an adaptive controller based on neural networks is used to compensate for the system .It is showed by the Lyapunov stability theorem that the tracking errors converge exponentially.The simulation results illustrate the efficiency of this method.