In recent years, the strapdown system has become the significant trend of the development of precision guided weapons. In order to effectively hit the lightly armored targets, researchers have done a series of studies on the impact angle control. However, most of them ignored the field-of-view constraint of the strapdown seeker. The existing impact angle control guidance laws with the field-of-view constraint have obvious drawbacks to some extent. For example, most of them are only applicable against nonmaneuvering targets and some of them suffer sudden hopping of guidance command due to the use of switching logic. Taking the strapdown seeker missile as the research object, this paper studies the field-of-view constrained impact angle control guidance problem against stationary targets, constant speed targets and maneuvering targets. According to the sliding mode control theory, two kinds of sliding surfaces are designed to make the missile achieve high precision attack under a desired impact angle within the field-of-view constraint. A quadratic barrier Lyapunov function and a logarithm barrier Lyapunov function are used to guarantee that the sliding surfaces designed for the impact angle constraint and the field-of-view constraint can converge to zero in finite time respectively. Then, a nonlinear extended state observer is proposed to estimate the unmeasurable disturbance of the system and alleviate the undesirable chattering by compensating it with the estimation of the disturbance. Finally, the feasibility of the proposed law is verified by numerical simulations.

Recently, multiple constraints have been considered in the design of guidance laws. Most of the existing impact angle control guidance laws considering the seeker’s field-of-view constraint are only applicable to constant speed missiles and have other limits to some extent. This paper is concerned with the field-of-view constrained impact angle control guidance law applied to variable speed missiles based on the sliding mode control theory. In the design of the sliding mode controller, we use a quadratic Lyapunov function to achieve the impact angle control. Moreover, we introduce an integral barrier Lyapunov function with an adaptive control item to address the field-of-view constraint and prevent the undesirable chattering caused by the disturbance of the nonlinear system. Then, the asymptotic stability of this close-looped system is verified. Eventually, numerical simulations are provided to demonstrate the performance of the proposed guidance law.

This paper proposes an intelligent control method based on Soft Actor-Critic (SAC) to address uncertainties faced by flight vehicles during flight. The method effectively reduces aerodynamic loads and enhances the reliability of structural strength under significant wind disturbances. A specific launch vehicle is taken as the research subject, and its dynamic model is established. A deep reinforcement learning (DRL) framework suitable for the attitude control problem is constructed, along with a corresponding training environment. A segmented reward function is designed: the initial stage emphasizes tracking accuracy, the middle stage, with a detrimental effect due to the high-altitude wind region, focuses on load relief, and the final stage gradually resumes following tracking accuracy on the basis of maintaining the effect of load relief. The reward function dynamically switches between stages using a time factor. The improved SAC algorithm is employed to train the agent over multiple epochs, ultimately resulting in an intelligent load relief attitude controller applicable to the launch vehicle. Simulation experiments demonstrate that this method effectively solves the attitude control problem under random wind disturbances, particularly reducing the aerodynamic loads of launch vehicles in the high-altitude wind region.