Title :
Robust nonlinear flight control of a high-performance aircraft
Author :
Wang, Qian ; Stengel, Robert F.
Author_Institution :
Dept. of Mech. Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
This paper considers probabilistic robust control of nonlinear uncertain systems. A combination of stochastic robustness and dynamic inversion is proposed for general systems that have a feedback-linearizable nominal system. In this paper, the stochastic robust nonlinear control approach is applied to a highly nonlinear complex aircraft model, the high-incidence research model (HIRM). The model addresses a high-angle-of-attack enhanced manual control problem. The aim of the flight control system is to give good handling qualities across the specified flight envelope without the use of gain scheduling and also to provide robustness to modeling uncertainties. The proposed stochastic robust nonlinear control explores the direct design of nonlinear flight control logic. Therefore, the final design accounts for all significant nonlinearities in the aircraft´s high-fidelity simulation model. The controller parameters are designed to minimize the probability of violating design specifications, which provides the design with good robustness in stability and performance subject to modeling uncertainties. The present design compares favorably with earlier controllers that were generated for a benchmark design competition.
Keywords :
Monte Carlo methods; aircraft control; control nonlinearities; control system synthesis; feedback; nonlinear control systems; parameter estimation; robust control; stochastic systems; uncertain systems; Monte Carlo simulation; dynamic inversion; feedback-linearizable nominal system; flight control logic; flight control system; high-fidelity simulation model; high-incidence research model; high-performance aircraft; nonlinear complex aircraft model; nonlinear control; nonlinear uncertain system; robust control; stochastic control; Aerospace control; Aircraft; Nonlinear dynamical systems; Robust control; Robust stability; Robustness; Stochastic processes; Stochastic systems; Uncertain systems; Uncertainty;
Journal_Title :
Control Systems Technology, IEEE Transactions on
DOI :
10.1109/TCST.2004.833651