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Sensor-Based Robust Incremental Three-Dimensional Guidance Law with Terminal Angle Constraint

Tuo Han, Qinglei Hu, Hyo‐Sang Shin, Antonios Tsourdos, Ming Xin

2021Journal of Guidance Control and Dynamics44 citationsDOIOpen Access PDF

Abstract

In this work, a robust incremental three-dimensional (3D) guidance law is proposed considering terminal angle constraint against maneuvering targets. As a stepping stone, the line-of-sight (LOS) tracking error dynamics is employed for the 3D guidance law design. A sliding variable is constructed such that its first-order derivative excludes the relative range in the perturbation, which avoids the unboundedness of system perturbation induced by target maneuvers near collision. A time-varying version of the sliding variable is designed to accelerate convergence of the LOS tracking errors and avoid large initial sliding variables. Then, two guidance laws are derived as a benchmark via the nonlinear dynamic inversion (NDI)-based sliding mode control (NDI-SMC) and NDI-based time-varying sliding mode control (NDI-TVSMC), respectively. To further improve guidance robustness with reduced system perturbation, the sensor-based incremental nonlinear dynamic inversion (INDI) control is used to design the INDI-SMC-based and INDI-TVSMC-based guidance laws. The sensor-based guidance laws exploit the LOS angular acceleration and guidance command output at the latest step, which result in smaller guidance gains to reject the perturbation than the NDI guidance laws. Numerical simulations in various cases and comparison studies are conducted to verify the effectiveness and robustness of the proposed method.

Topics & Concepts

Control theory (sociology)Robustness (evolution)Perturbation (astronomy)Nonlinear systemSliding mode controlComputer scienceLawInversion (geology)PhysicsControl (management)Artificial intelligenceBiochemistryChemistryBiologyStructural basinGenePolitical scienceQuantum mechanicsPaleontologyGuidance and Control SystemsAdaptive Control of Nonlinear SystemsRobotic Path Planning Algorithms