Modeling and Analysis of Multiple Engine Aircraft Configurations for Fault Tolerant Control

A formal framework is presented that allows for the analysis of the potential for using engine thrust control for aircraft actuator failure accommodation. Three sets of parameters have been identified as critical: number of engines and their position, engine thrust and throttle dynamics, and type and severity of the actuator failure. A mathematical model was developed that allows for the determination of the values of some of the parameters when the others are imposed such as determining the thrust control authority when the engine locations and Euler angles are known. Additionally, the engine locations can be determined when the thrust control authority and engine Euler angles are known and the engine Euler angles can be determined when the engine locations and thrust control authority are known. A MATLAB/Simulink simulation environment was built around a model of a large transport that can accommodate up to ten engines at different locations. A fuzzy logic controller was designed and employed for failure accommodation. The fuzzy logic controller utilizes the pilot lateral, longitudinal, and directional commands as well as the aircraft\u27s pitch attitude, roll attitude, yaw attitude and respective angular rates as the inputs to the system and provides throttle commands for each engine based on its location with respect to the aircraft\u27s center of mass. Failures of varying severity on the rudder, left or right aileron, and left or right elevator were implemented. The controller was capable of accommodating an extremely severe aileron failure and moderately severe rudder failure without additional pilot input. The controller was capable of mitigating some of the pilot command required for a moderate elevator failure. The simulation environment was used to verify the analytical results and to demonstrate the fault tolerant capabilities of multiple engine configurations. It proved to be a flexible and efficient tool for analysis and control system development

Load allocation for optimal risk management in systems with incipient failure modes

The development and implementation challenges associated with a proposed load allocation paradigm for fault risk assessment and system health management based on uncertain fault diagnostic and failure prognostic information are investigated. Health management actions are formulated in terms of a value associated with improving system reliability, and a cost associated with inducing deviations from a system's nominal performance. Three simulated case study systems are considered to highlight some of the fundamental challenges of formulating and solving an optimization on the space of available supervisory control actions in the described health management architecture. Repeated simulation studies on the three case-study systems are used to illustrate an empirical approach for tuning the conservatism of health management policies by way of adjusting risk assessment metrics in the proposed health management paradigm. The implementation and testing of a real-world prognostic system is presented to illustrate model development challenges not directly addressed in the analysis of the simulated case study systems. Real-time battery charge depletion prediction for a small unmanned aerial vehicle is considered in the real-world case study. An architecture for offline testing of prognostics and decision making algorithms is explained to facilitate empirical tuning of risk assessment metrics and health management policies, as was demonstrated for the three simulated case study systems.Ph.D