An Iterative Dynamic Control Allocation Formulation for Hypersonic Vehicles with Asymmetrical Input Limitations on Magnitude and Rate

Abstract

Hypersonic glide vehicles (HGVs) present unique control challenges due to high-speed atmospheric interactions, state-dependent actuator constraints, and thermal loads on control surfaces. This paper introduces a iterative control allocation approach tailored to meet these demands, addressing asymmetric control input limits, actuator coupling, and state-dependent thermal constraints. Traditional methods, such as pseudoinverse-based approaches and quadratic programming, when applied to complex overactuated systems like HGVs, either fail to fully exploit the available moment set or lack real-time guarantees for embedded systems with limited computing resources, thus limiting their applicability to hypersonic vehicles. Our proposed algorithm iteratively optimizes control inputs to achieve desired moment commands while dynamically adjusting for constraints on input magnitude and rate. By incorporating thermal load-dependent soft constraints and leveraging prior flight dynamics knowledge on actuator coupling, this method enhances both vehicle performance and structural integrity during high-speed maneuvers. We applied and validated the algorithm using DLR's Generic Hypersonic Glide Vehicle 2 (GHGV-2) concept, with simulation results demonstrating the algorithm’s efficiency in maintaining control authority.