Model Reference Control for Reducing Pilot-Induced Oscillation Tendencies

Abstract

Lags between pilot inputs and aircraft responses may lead to a pilot–vehicle system entering into a pilot-induced oscillation. A model reference control element can compensate for these lags, avoiding pilot-induced oscillations and improving tracking performance. Neural network compensation drives the combined controller–plant system to exhibit a closed-loop response similar to that of an idealized system, immune to the factors that trigger pilot-induced oscillations. Actuator rate limiting has been a historically ubiquitous cause of pilot-induced oscillations; meanwhile, aeroelastic effects pose a threat to future lightweight, flexible aircraft designs. Model reference control can reduce pilot-induced oscillation tendencies caused by either of these factors. This paper presents the methods used to train the model reference controller, including conditions for system stability under model reference control. It then showcases results from a pair of simulation experiments applying the control design to compensate for rate limiting and aeroelasticity, respectively. Results demonstrate that the model reference control scheme reduces pilot-induced oscillation tendencies and improves closed-loop tracking performance.