Development Of Formation Flight Control Algorithms Using 3 Yf 22 Flying Models

The main objective of this project was to provide a flight demonstration of formation control using UAV research aircraft models. This document will describe the efforts leading to the design, construction, and flight testing of formation control laws using three YF-22 research UAVs designed, built, and instrumented at West Virginia University (WVU). In the selected formation configuration, a radio control (R/C) pilot maintains ground control of the 'leader' aircraft while two autonomous 'follower' aircraft are required to maintain a pre-defined position and orientation with respect to the 'leader' aircraft. The report is organized as follows. First, a description of the aircraft test-bed construction and on-board payload systems will be provided. The following sections will describe the overall design of the formation control laws. Specifically, this design was based on a set of inner and outer loop control laws using a NLDI (non Linear Dynamic Inversion) approach. The implementation of the controller design featured a mathematical model obtained directly from flight data through a PID (Parameter Identification) study. Additional sections will provide a description of the on-board flight control software and simulation work prior to the flight testing activities. A final section will describe the results from an extensive flight testing program. The flight testing activities were articulated in several flight testing of 2-aircraft and 3-aircraft formations.

Covering the design, development, operation and mission profiles of unmanned aircraft systems, this single, comprehensive volume forms a complete, stand-alone reference on the topic. The volume integrates with the online Wiley Encyclopedia of Aerospace Engineering, providing many new and updated articles for existing subscribers to that work.

Automating the control of an aircraft flying in formation necessitates the extension of the theory of formation flight control to allow for three dimensional maneuvers. The formation was modeled as a two-aircraft, leader and wingspan, formation. Both aircraft has its own three dimensional, rotating and translating, Cartesian axes system, with special attention being given to the motion of the leader in relation to the wingspan. The controller operated using the equations of motion expressed in the rotating reference frame of the wing aircraft. The control system has seven states, three inputs and three disturbance signals to model the dynamics of the formation in three dimensional space. The control law employed was the feedback of the difference between in actual separation distance and the commanded separation distance to affect changes in thrust, lift, and roll rate. The control system incorporated proportional, integral, and derivative control elements, each with separate gains, to achieve and maintain the specified formation geometry despite various maneuvers flown by the leader. Simulated maneuvers included: an initial displacement of the wingspan away from the formation geometry, and changes in the leader's velocity, altitude, and heading. For each maneuver, the controller performance was sufficient to maintain the commanded formation geometry.

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The 1st edition of Aircraft Dynamics: from Modeling to Simulation by Marcello R. Napolitano is an innovative textbook with specific features for assisting, motivating and engaging aeronautical/aerospace engineering students in the challenging task of understanding the basic principles of aircraft dynamics and the necessary skills for the modeling of the aerodynamic and thrust forces and moments. Additionally the textbook provides a detailed introduction to the development of simple but very effective simulation environments for today demanding students as well as professionals. The book contains an abundance of real life students sample problems and problems along with very useful Matlab codes.

This monograph introduces recent developments in formation control of distributed-agent systems. Eschewing the traditional concern with the dynamic characteristics of individual agents, the book proposes a treatment that studies the formation control problem in terms of interactions among agents including factors such as sensing topology, communication and actuation topologies, and computations. Keeping pace with recent technological advancements in control, communications, sensing and computation that have begun to bring the applications of distributed-systems theory out of the industrial sphere and into that of day-to-day life, this monograph provides distributed control algorithms for a group of agents that may behave together. Unlike traditional control laws that usually require measurements with respect to a global coordinate frame and communications between a centralized operation center and agents, this book provides control laws that require only relative measurements and communications between agents without interaction with a centralized operator. Since the control algorithms presented in this book do not require any global sensing and any information exchanges with a centralized operation center, they can be realized in a fully distributed way, which significantly reduces the operation and implementation costs of a group of agents. Formation Control will give both students and researchers interested in pursuing this field a good grounding on which to base their work.

Close formation flight is extensively investigated from the perspectives of dynamic modeling, aerodynamic analysis, and control design. A lifting-line based aerodynamic model is presented to describe the aerodynamic coupling between two aircraft in close formation. The introduced aerodynamic model is validated via the comparison with a single horseshoe vortex-based model, a vortex lattice method-based model, and experimental results. Comprehensive analysis is thereafter conducted to investigate the drag reduction variations with respect to different relative positions, angles of attack, sideslip angles, and leader-to-follower wing span ratios. The analysis indicates that the drag reduction performance of close formation flight is sensitive to the formation position accuracy. Additionally, basic requirements are formulated for close formation flight control. In terms of the proposed aerodynamic model, a linear robust adaptive formation controller is developed specifically for close formation at level and straight flight. The proposed robust adaptive controller shows dramatic increase in both transient performance and robustness against model uncertainties and disturbances. The nonlinear robust close formation control problem is thereafter studied under a leader-following architecture. Nonlinear robust close formation controllers with different considerations are proposed based on a command filtered backstepping method and an uncertainty and disturbance estimation technique. The proposed nonlinear robust formation controllers could accommodate more complex flight scenarios, for instance, different flight maneuvers and close formation of more than three aircraft. With the increase of the number of aircraft in close formation, a leader-following formation controller might become less and less efficient. Regarding the efficiency degradation issue of leader-following formation controllers, two cooperative control algorithms are introduced, which exhibit better tracking performance for close formation of a large number of aircraft. Extensive simulations are carried out to validate the effectiveness of all proposed close formation control algorithms.