Publications [#289454] of Silvia Ferrari

Papers Published

1. Chandramohan, R; Steck, JE; Rokhsaz, K; Ferrari, S, Adaptive critic flight control for a general aviation aircraft: Simulations for the beech bonanza fly-by-wire test bed, Collection of Technical Papers 2007 Aiaa Infotech at Aerospace Conference, vol. 1 (January, 2007), pp. 840-855 [doi]
   (last updated on 2021/09/05)

   Abstract:
   An adaptive and reconfigurable flight control system is developed for a general aviation aircraft. The adaptive critic method developed by Ferrari and Stengel is adapted to the GA aircraft. The flight control system uses artificial neural networks as the adaptive element. They are developed using a two step procedure utilizing a pre-training phase and an online training phase. In the pre-training phase the architecture and initial weights of the neural network are determined based on gain scheduled linear control designs. A set of local gains for the linearized model of the plant is obtained at different points on the velocity v/s altitude envelope using the LQR method. The pre-training phase guarantees that the neural network controller meets the performance specifications of the linear controllers at the design points. Online training uses a dual heuristic adaptive critic architecture that trains the networks to meet performance specifications in the presence of nonlinearities and control failures. The control system developed is implemented for a three-degree-of- freedom longitudinal aircraft simulation. The results show that the adaptive control system meets the performance requirements, specified in terms of the damping ratio of the phugoid and short period modes, in the presence of nonlinearities. The neural network controller also compensates for partial elevator and thrust failures. It is also observed that the neural network controller meets the performance specification in the presence of large modeling errors.