The Design of Adaptive Integrated Guidance and Control Subjected to State Constraints and Multiple Uncertainties

This paper focuses on adaptive dynamic surface composite control subjected to state constraints and multiple uncertainties in integrated guidance and control (IGC) design for skid-to-turn missiles. The novel IGC algorithm incorporates adaptive dynamic surface composite control with the barrier Lyapunov function. Composite control in this paper takes a superior approach by introducing the estimated information of the system states from the series-parallel estimation model into the neural network under the framework of adaptive dynamic surface control to achieve composite learning, which makes the algorithm learn more accurately for system disturbance. Meanwhile, the saturation function and the barrier Lyapunov function (BLF) ensure that the system state satisfies the constraints. The effectiveness of the IGC scheme is verified by numerical simulation.