A reaching law based neural network terminal sliding-mode guidance law design

A nonsingular terminal guidance law is proposed for dual-controlled missile with tails and reaction jets based on power rate reaching law and neural network terminal sliding mode control (TSMC). By combining nonsingular terminal sliding mode control (NTSMC) with power rate reaching law, the guidance law improves the reaching rate of system states to sliding surface with less control command. Also, it makes the line-of-sight (LOS) angular rate converge to zero in a finite time. The disturbance is compensated and monitored by using online learning neural network under consideration of model uncertainty and the effect of target maneuvering, the robustness of the control systems is therefore improved. Simulation results show that, the guidance law can make the system states converge to zero in a limited time, and can achieve better system performance in guaranteeing system robustness.