Automatic landing system using neural networks and radio-technical subsystems

The paper focuses on the design of a new automatic landing system (ALS) in longitudinal plane; the new ALS controls the aircraft trajectory and longitudinal velocity. Aircraft control is achieved by means of a proportional-integral (PI) controller and the instrumental landing system - the first phase of landing (the glide slope) and a proportional-integral-derivative (PID) controller together with a radio-altimeter - the second phase of landing (the flare); both controllers modify the reference model associated with aircraft pitch angle. The control of the pitch angle and longitudinal velocity is performed by a neural network adaptive control system, based on the dynamic inversion concept, having the following as components: a linear dynamic compensator, a linear observer, reference models, and a Pseudo control hedging (PCH) block. The theoretical results are software implemented and validated by complex numerical simulations; compared with other ALSs having the same radio-technical subsystems but with conventional or fuzzy controllers for the control of aircraft pitch angle and longitudinal velocity, the architecture designed in this paper is characterized by much smaller overshoots and stationary errors.