Purpose The purpose of this paper is to develop and implement a general sensor model under normal and abnormal operational conditions including nine functional categories (FCs) to provide additional tools for the design, testing and evaluation of unmanned aerial systems within the West Virginia University unmanned air systems (UAS) simulation environment. Design/methodology/approach The characteristics under normal and abnormal operation of various types of sensors typically used for UAS control are classified within nine FCs. A general and comprehensive framework for sensor modeling is defined as a sequential alteration of the exact value of the measurand corresponding to each FC. Simple mathematical and logical algorithms are used in this process. Each FC is characterized by several parameters, which may be maintained constant or may vary during simulation. The user has maximum flexibility in selecting values for the parameters within and outside sensor design ranges. These values can be set to change at pre-defined moments, such that permanent and intermittent scenarios can be simulated. Sensor outputs are integrated with the autonomous flight simulation allowing for evaluation and analysis of control laws. Findings The developed sensor model can provide the desirable levels of realism necessary for assessing UAS behavior and dynamic response under sensor failure conditions, as well as evaluating the performance of autonomous flight control laws. Research limitations/implications Due to its generality and flexibility, the proposed sensor model allows detailed insight into the dynamic implications of sensor functionality on the performance of control algorithms. It may open new directions for investigating the synergistic interactions between sensors and control systems and lead to improvements in both areas. Practical implications The implementation of the proposed sensor model provides a valuable and flexible simulation tool that can support system design for safety purposes. Specifically, it can address directly the analysis and design of fault tolerant flight control laws for autonomous UASs. The proposed model can be easily customized to be used for different complex dynamic systems. Originality/value In this paper, information on sensor functionality is fused and organized to develop a general and comprehensive framework for sensor modeling at normal and abnormal operational conditions. The implementation of the proposed approach enhances significantly the capability of the UAS simulation environment to address important issues related to the design of control laws with high performance and desirable robustness for safety purposes.

The main objective of this thesis is to develop new capabilities within the West Virginia University (WVU) unmanned aerial systems (UAS) simulation environment for the design and analysis of fault tolerant control laws on small sized unmanned aerial vehicles (UAVs). An aerodynamic model for an electric powered UAV is developed using a vortex lattice method implemented within the computational design package Tornado. One-dimensional look-up tables are developed for the main stability and control derivatives, which are then used to calculate linear aerodynamic forces and moments for the nonlinear aircraft equations of motion. Flight data are used for model verification and tuning. The characteristics under normal and abnormal operation of various types of sensors typically used for UAV control are classified under nine functional categories. A general and comprehensive framework for sensor modeling is defined as a sequential alteration of the exact value of the measurand corresponding to each functional category. Simple mathematical and logical algorithms are formulated and used in this process. Each functional category is characterized by several parameters, which may be maintained constant or may vary during simulation. The user has maximum flexibility in selecting values for the parameters within and outside sensor design ranges. These values can be set to change at pre-defined moments, such that permanent and intermittent scenarios can be simulated. The aircraft and sensor models are then integrated with the WVU UAS simulation environment, which is created using MATLAB/Simulink for the computational part and FlightGear for the visualization of the aircraft and scenery. A simple user-friendly graphical interface is designed to allow for detailed simulation scenario setup. The functionality of the developed models is illustrated through a limited analysis of the effects of sensor abnormal operation on the trajectory tracking performance of autonomous UAV. A composite metric is used for aircraft performance assessment based on both trajectory tracking errors and control activity. The targeted sensors are the gyroscopes providing angular rate measurements and the global positioning system providing position and velocity information. These sensors are instrumental in the inner and outer control loops, respectively, which characterize the typical control architecture for autonomous trajectory tracking. Due to its generality and flexibility, the proposed sensor model provides detailed insight into the dynamic implications of sensor functionality on the performance of control algorithms. It facilitates the investigation of the synergistic interactions between sensors and control systems and may lead to improvements in both areas.