Abstract

The paper presents a qualitatively new approach to terminal guidance at the final trajectory section for the surface-to-surface class aerial vehicles. The proposed structure of the adaptive control system for an aerial vehicle is based on the multi-step terminal guidance algorithm. Adaptive corrections to the control coefficients were calculated using the developed method for identifying the wind disturbances based on the machine learning models. The work describes technique to form an intelligent algorithm for identifying intensity and direction of the wind load acting on the aerial vehicle in flight. Options of the machine learning models used in the guidance system intelligent block were investigated; their operation results are presented; and the comparative analysis has been carried out. The adaptive guidance system operation procedure is demonstrated on a typical model of the aerial vehicle flying in the atmosphere and targeting a fixed object. Numerical simulation results are presented, and possibility of using such an algorithm and implementing the described system are demonstrated.

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