Abstract: Facing the demands of high-density launch operations, reusability, and post-failure mission reconfiguration, launch vehicle control systems are confronted with several fundamental challenges, including strongly nonlinear and time-varying dynamics, actual deviations that may exceed predetermined envelopes, and the inherent difficulty of balancing multi-task, multi-constraint online optimization. Conventional approaches that rely on nominal models and offline design are increasingly incapable of simultaneously satisfying the requirements for performance, reliability, and autonomy. The core value of intelligent control lies in transforming offline design for deviation envelopes into online optimization tailored to specific states and operating conditions—a transition that represents an inevitable trajectory in the advancement of launch vehicle technologies. This paper provides a systematic review of intelligent control technologies for launch vehicles, covering four key aspects: intelligent dynamic modeling, intelligent navigation and guidance, intelligent control, and intelligent health management. We comprehensively survey the technical routes and representative accomplishments that integrate model-driven and data-driven methodologies, and critically examine the advantages, applicability conditions, and remaining theoretical and engineering bottlenecks of various intelligent approaches relative to their classical counterparts. Furthermore, we identify that the engineering deployment of intelligent control still confronts several core challenges, including interpretability and trustworthiness verification, algorithm deployment under onboard computational constraints, and stability guarantees for learning-based methods in safety-critical systems. Finally, we present an outlook on future research directions, with the aim of providing valuable references for the development of China's next-generation intelligent launch vehicles.

Key words: launch vehicle, intelligent control, intelligent navigation and guidance, power failure, health management