基于自适应动态规划的鲁棒最优导弹自动驾驶仪滑模控制

Robust Optimal Sliding Mode Control of Missile Autopilot Based on Adaptive Dynamic Programming

利用自适应动态规划算法,研究了带有扰动的导弹自动驾驶仪系统的鲁棒最优控制问题。首先,设计了非线性扰动观测器估计系统中的未知扰动;接着,考虑一类积分滑模面,根据扰动观测器的输出,设计积分滑模控制器,使得系统沿着滑模面进入滑动模态运动;然后,针对等效滑动模态系统,设计带有新权值更新律的评价网络,利用自适应动态规划技术自适应学习最优控制律,通过Lyapunov方法证明了闭环系统的稳定性和权值估计值的收敛性;最后,运用导弹自动驾驶仪系统验证了算法的可行性和有效性。

This paper aims to develop a robust optimal control method for missile autopilot systems suffering from external disturbances by using adaptive dynamic programming algorithm.First,a nonlinear disturbance observer is designed to estimate unknown external disturbance.Then,considering an integral sliding mode surface and the output of disturbance observeran integral sliding mode controller is designed to make the system enter into sliding mode motion along the sliding surface.Subsequently,for equivalent sliding mode dynamic systems,a critic network is constructed with a novel weight update law,and the adaptive dynamic programming technique is employed to learn an optimal controller.With the Lyapunov's methodthe stability of closed-loop system and the convergence of estimation weight for critic network are proved.Finally,the missile autopilot system is used to verify the effectiveness and feasibility of the designed approach.