Online Optimal Midcourse Guidance Using Sequential Convex Programming

Midcourse guidance plays a crucial role in long range air-defence interception missions by guiding the interceptor from the launch site to the vicinity of the target, allowing the onboard seeker to lock onto the target, and facilitating successful interception during the terminal phase. In recent years, the demand for advanced optimal guidance techniques has surged in response to the development of new classes of targets characterized by high maneuverability and hypersonic speed, leading to increased uncertainty in predicting the impact point. The thesis aims to formulate and implement an online guidance algorithm that addresses the challenges posed by these new targets. The advantage of online guidance lies in its ability to recurrently generate optimal trajectory during the interceptor’s flight as the mission environment evolves and more precise target information becomes available. These trajectories are required to be dynamically feasible, adhere to path and terminal constraints, and be generated reliably and time efficiently in real-time. Consequently, the interceptor’s autopilot is continually updated with the latest optimal control commands. Firstly, a 2DoF dynamic model of the interceptor’s motion in the vertical plane is defined, with aerodynamic data of the trimmed system provided in the form of look-up table. Benchmark trajectories are then generated using a well-known Gauss pseudospectral collocation method, which discretize and solve the optimization problem as a nonlinear program (NLP). A Successive convexification algorithm is adopted to solve trajectory optimization due to its high solution accuracy and computational speed. The nonlinear interceptor dynamic model is convexified, discretized and iteratively solved by a Second Order Cone Programming (SOCP) solver until the optimal solution of the linearized problem correspond to the optimal solution of the nonlinear problem. To handle thrust cut-offs and mass discontinuities of the interceptor model due to staging and gliding phases, a multiphase discretization scheme is proposed. Simulation results demonstrate that optimal solution of the convex optimization closely agrees with the solution obtained by the pseudospectral method. In conclusion, the algorithm is implemented within a Model Predictive Control (MPC) framework to demonstrate its online trajectory planning and guidance capability.