Nonlinear Control Allocation for a High-Performance Tailless Aircraft with Innovative Control Effectors

Abstract

Conventional linear control allocation (LCA) methods fail to provide satisfactory performance in flight control systems (FCS) for aircraft with highly nonlinear and coupled control effector suites, especially for tailless aircraft with strong interactions between control effectors. This thesis implements an incremental nonlinear control allocation (INCA) approach that can capture nonlinearities and interactions of control effectors, while being solvable with computationally efficient LCA algorithms. This makes INCA suitable for real-time control allocation in FCS. This incremental reformulation of the control allocation problem is based on a Jacobian model of the control effectors, and relies on angular acceleration measurements to reduce model dependency. In addition, real-time measurements of the actuator positions mitigate typical problems related to couplings between control allocators and actuator dynamics. In this paper, LCA- and INCA-based nonlinear FCS are designed for the Innovative Control Effectors (ICE) aircraft, a highly maneuverable tailless aircraft with 13 highly nonlinear, interacting and axis-coupled control effectors. Real-time simulation results showed that INCA dramatically improves tracking and control allocation performance with respect to LCA methods, thus improving maneuverability and exploiting the full potential of innovative control effector suites. Additionally, a sensitivity analysis revealed that the INCA method is highly robust against Jacobian model mismatch.