Abstract:This paper presents an integrated guidance and control (IGC) law for the strapdown homing missile with consideration of the field-of-view (FOV) constraint and actuator saturation. Given that the commonly-required guidance information, such as the inertial line-of-sight (LOS) angle and/or its angular rate, cannot be measured by the strapdown seeker, a detailed IGC model considering the gravity and timevarying missile velocity is first derived based on the only measurable information, the body-LOS (BLOS) angle. … Show more
“…Although the future course of action of the target in [16], as a type of uncertainty, cannot be predicted, the effect of the target maneuver can be counteracted by utilizing adaptive control techniques. Meanwhile, many control algorithms have been reported based on adaptive control [17], DSC [18,19], command filtered control [20], sliding mode control [21,22], barrier Lyapunov function (BLF) [23,24], and a fixed-time differentiator [25] for the constrained variables of IGC system. In [26], a three-dimensional integrated guidance and control law is developed, which relies on the advantage of dynamic surface control and extended state observer techniques to address input saturation and actuator failure.…”
This paper investigates a novel robust adaptive dynamic surface control scheme based on the barrier Lyapunov function (BLF), online composite learning, disturbance observer, and improved saturation function. It is mainly designed for a class of skid-to-turn (STT) interceptor integrated guidance and control (IGC) design problems under multi-source uncertainties, state constraints, and input saturation. The serial-parallel estimation model used in this study estimates the system states and provides “critic” information for the neural network and disturbance observer; then, these three are combined to realize online composite learning of the multiple uncertainties of the system and improve the interception accuracy. In addition, the state and input constraints are resolved by adopting the BLF and the improved saturation function, while the design of the auxiliary system ensures stability. Finally, a series of simulation results show that the proposed IGC scheme with a direct-hit intercept strategy achieves a satisfactory effect, demonstrating the validity and robustness of the scheme.
“…Although the future course of action of the target in [16], as a type of uncertainty, cannot be predicted, the effect of the target maneuver can be counteracted by utilizing adaptive control techniques. Meanwhile, many control algorithms have been reported based on adaptive control [17], DSC [18,19], command filtered control [20], sliding mode control [21,22], barrier Lyapunov function (BLF) [23,24], and a fixed-time differentiator [25] for the constrained variables of IGC system. In [26], a three-dimensional integrated guidance and control law is developed, which relies on the advantage of dynamic surface control and extended state observer techniques to address input saturation and actuator failure.…”
This paper investigates a novel robust adaptive dynamic surface control scheme based on the barrier Lyapunov function (BLF), online composite learning, disturbance observer, and improved saturation function. It is mainly designed for a class of skid-to-turn (STT) interceptor integrated guidance and control (IGC) design problems under multi-source uncertainties, state constraints, and input saturation. The serial-parallel estimation model used in this study estimates the system states and provides “critic” information for the neural network and disturbance observer; then, these three are combined to realize online composite learning of the multiple uncertainties of the system and improve the interception accuracy. In addition, the state and input constraints are resolved by adopting the BLF and the improved saturation function, while the design of the auxiliary system ensures stability. Finally, a series of simulation results show that the proposed IGC scheme with a direct-hit intercept strategy achieves a satisfactory effect, demonstrating the validity and robustness of the scheme.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.