Successive Convexification for Real-Time Six-Degree-of-Freedom Powered Descent Guidance with State-Triggered Constraints

What is it about?

This paper presents an algorithm that solves a generalized rocket landing guidance problem using an iterative optimization technique known as successive convexification. The most important contribution of this paper is the introduction of a continuous formulation for state-triggered constraints (STCs) -- constraints that are conditionally enforced when a state-dependent condition is satisfied. Such constraints are typically implemented using discrete decision variables (e.g. mixed-integer programming) which introduce a layer of computational complexity that is not amenable to real-time computation. Our formulation allows such constraints to be formulated in a continuous optimization framework capable of computing solutions in real-time. STCs enable rocket landing applications containing velocity-triggered angle of attack constraints and range-triggered line of sight constraints. Two secondary contributions of this paper are the introduction of a free-ignition-time modification that allows the engine ignition time to be optimized, and a simplified aerodynamic model that captures the basic effects of lift and drag on the rocket.

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