Incremental Nonlinear Dynamic Inversion control with Flight Envelope Protection for the Flying-V

To reduce the impact of aviation on the environment, technological innovations, such as the Flying-V are required. The Flying-V is a proposed commercial flying wing, which uses the Airbus A350-900 as reference aircraft. In this work, a Flight Control system for the Flying-V is proposed with a longitudinal ��∗ control law, and a Rate Control...

Multi-objective Design and Performance Analysis of Incremental Control Allocation-based Flight Control Laws

This paper proposes an extension to the traditional flight path reconstruction filter to simultaneously reconstruct the aircraft rigid body states together with modal amplitudes and velocities of the structure. To achieve this, the filter makes use of additional accelerometers, gyroscopes and strain gauges placed across the aircraft structure....

Adaptive Incremental Nonlinear Dynamic Inversion Flight Control for Consistent Handling Qualities

Control augmentation systems based on Incremental Nonlinear Dynamic Inversion (INDI) are able to provide high-performance nonlinear control without a holistic model. Considering an angular rate control law for a fixed-wing aircraft, only a control effectiveness (CE) model and angular acceleration measurement feedback is required. Despite...

Robust Stability and Performance Analysis of Incremental Dynamic Inversion-based Flight Control Laws

Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control law design strategy that is based on the principles of feedback linearization. Contrary to its non-incremental counterpart (NDI), this design method does not rely on the availability of a high-fidelity on-board model of the airframe dynamics and is robust to aerodynamic...

Flight Control Law Design using Hybrid Incremental Nonlinear Dynamic Inversion

Incremental Nonlinear Dynamic Inversion (INDI) is a sensor-based control strategy, which has shown robustness against model uncertainties on various aerospace platforms. The sensor-based nature of the method brings attractive properties, which has made it popular in the last decade. INDI globally linearizes the system by making use of control...

Safe Curriculum Learning for Linear Systems with Parametric Unknowns in Primary Flight Control

Safe Curriculum Learning aims at improving safety and efficiency aspects of Reinforcement Learning (RL). Curricular RL approaches divide a task into stages of increasing complexity in order to increase efficiency. This paper proposes a black box safe curriculum learning architecture applicable to systems with parametric unknowns. The agent...

Optimal Variable Wing Camber Control using Incremental Nonlinear Dynamic Inversion

Flight control systems enable the improvement of natural flying qualities and airframe performance of an aircraft. In this article, an incremental optimization control scheme is proposed to optimize a given performance objective set by the designer in an online fashion using limited model information. This scheme is applied to improve the...

Safe Curriculum Learning for Optimal Flight Control of Unmanned Aerial Vehicles with Uncertain System Dynamics

Reinforcement learning (RL) enables the autonomous formation of optimal, adaptive control laws for systems with complex, uncertain dynamics. This process generally requires a learning agent to directly interact with the system in an online fashion. However, if the system is safety-critical, such as an Unmanned Aerial Vehicle (UAV), learning may...