String Instabilities in Formation Flight: Limitations Due to Integral Constraints

2004 ◽  
Vol 126 (4) ◽  
pp. 873-879 ◽  
Author(s):  
P. Seiler ◽  
A. Pant ◽  
J. K. Hedrick
Keyword(s):  
Flight Control ◽  
Formation Control ◽  
Energy Savings ◽  
Feedback Loops ◽  
Formation Flight ◽  
Control Laws ◽  
Aerodynamic Efficiency ◽  
Preceding Vehicle ◽  
Specific Control ◽  
Theoretical Results

Flying in formation improves aerodynamic efficiency and, consequently, leads to an energy savings. One strategy for formation control is to follow the preceding vehicle. Many researchers have shown through simulation results and analysis of specific control laws that this strategy leads to amplification of disturbances as they propagate through the formation. This effect is known as string instability. In this paper, we show that string instability is due to a fundamental constraint on coupled feedback loops. The tradeoffs imposed by this constraint imply that predecessor following is an inherently poor strategy for formation flight control. Finally, we present two examples that demonstrate the theoretical results.

Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation

2017 ◽  
Vol 121 (1241) ◽  
pp. 877-900 ◽  
Author(s):  
Y. Xu ◽  
Z. Zhen
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Flight Control ◽  
Control Strategy ◽  
Formation Control ◽  
Parametric Uncertainty ◽  
Lyapunov Theory ◽  
Formation Flight ◽  
Flight Control System ◽  
Multiple Uavs

ABSTRACTThe Unmanned Aerial Vehicles (UAVs) become more and more popular due to various potential application fields. This paper studies the distributed leader-follower formation flight control problem of multiple UAVs with uncertain parameters for both the leader and followers. This problem has not been addressed in the literature. Most of the existing literature considers the leader-follower formation control strategy with parametric uncertainty for the followers. However, they do not take the leader parametric uncertainty into account. Meanwhile, the distributed control strategy depends on less information interactions and is more likely to avoid information conflict. The dynamic model of the UAVs is established based on the aerodynamic parameters. The establishment of the topology structure between a collection of UAVs is based on the algebraic graph theory. To handle the parametric uncertainty of the UAVs dynamics, a multivariable model reference adaptive control (MRAC) method is addressed to design the control law, which enables follower UAVs to track the leader UAV. The stability of the formation flight control system is proved by the Lyapunov theory. Simulation results show that the proposed distributed adaptive leader-following formation flight control system has stronger robustness and adaptivity than the fixed control system, as well as the existing adaptive control system.

Aerial Robot Formation Control via Pigeon-Inspired Optimization

2020 ◽  
pp. 1143-1180
Author(s):  
Haibin Duan
Keyword(s):  
Flight Control ◽  
Formation Control ◽  
Time Discretization ◽  
Population Based ◽  
Global Optimum ◽  
Formation Flight ◽  
Control Parameters ◽  
Aerial Robot ◽  
Swarm Intelligence Optimization ◽  
Prediction Control

Formation flight for aerial robots is a rather complicated global optimum problem. Three formation flight control problems are introduced in this chapter, respectively, underlying controller parameter optimization, basic formation control and formation reconfiguration control. Two methods, Model Prediction Control (MPC) and Control Parameterization and Time Discretization (CPTD), are applied to solve the above problems. However, the selection of appropriate control parameters is still a barrier. Pigeon-Inspired Optimization (PIO) is a new swarm intelligence optimization algorithm, which is inspired by the behavior of homing pigeons. Owning to its better performance of global exploration than others, the thoughts of PIO are applied to the control field to optimize the control parameters in the three aerial robot formation problems, to minimize the value of the cost function. Furthermore, comparative experimental results with a popular population-based algorithm called Particle Swarm Optimization (PSO) are given to show the feasibility, validity and superiority of PIO.

Design of formation control laws for manoeuvred flight

2004 ◽  
Vol 108 (1081) ◽  
pp. 125-134 ◽  
Author(s):  
G. Campa ◽  
S. Wan ◽  
M. R. Napolitano ◽  
B. Seanor ◽  
M. L. Fravolini
Keyword(s):  
Nonlinear Model ◽  
Formation Control ◽  
Formation Flight ◽  
Control Synthesis ◽  
Simulation Studies ◽  
West Virginia University ◽  
Control Laws ◽  
Control Scheme ◽  
System Robustness ◽  
Position And Orientation

Abstract This paper presents identification, control synthesis and simulation results for an YF-22 aircraft model designed, built, and instrumented at West Virginia University. The ultimate goal of the project is the experimental demonstration of formation flight for a set of 3 of the above models. In the planned flight configuration, a pilot on the ground maintains controls of the leader aircraft while a wingman aircraft is required to maintain a pre-defined position and orientation with respect to the leader. The identification of both a linear model and a nonlinear model of the aircraft from flight data is discussed first. Then, the design of the control scheme is presented and discussed with an emphasis on the amount of information, relative to the leader aircraft, needed by the wingman to maintain formation. Using the developed nonlinear model, the control laws for a maneuvered flight of the formation are then simulated with Simulink® and displayed with the Virtual Reality Toolbox®. Simulation studies have been performed to evaluate the effects of specific parameters and the system robustness to atmospheric turbulence. The conclusions from this analysis have allowed the formulation of specific guidelines for the design of the electronic payload for formation flight.

A Virtual Environment for Simulation of Formation Flight

2015 ◽  
Vol 713-715 ◽  
pp. 263-266
Author(s):  
Zhen Dong Xu ◽  
Tao Shang ◽  
Rong Min Sun ◽  
De Ming Wang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Virtual Environment ◽  
Flight Control ◽  
Video Camera ◽  
Formation Flight ◽  
Nonlinear Characteristics ◽  
Control Laws ◽  
Aerial Vehicles ◽  
Highly Nonlinear ◽  
Formation Keeping

This paper presents the design of Unmanned Aerial Vehicles (UAVs) formation flight control laws and then the virtual Environment setup of a nice structure for close formation flight. The images of the target airplane projected on the video-camera plane of the follower airplane are captured and processed into vision information The simulation setup includes airplane dynamics, autopilots and formation keeping controller and module that creates virtual environment for the simulation of the vision software called Unity3D. The UKF is applied to the relative motion estimator due to the highly nonlinear characteristics of the problem.

Formation control of aerial robots using virtual structure and new fuzzy-based self-tuning synchronization

2016 ◽  
Vol 39 (12) ◽  
pp. 1906-1919 ◽  
Author(s):  
Y Abbasi ◽  
S. Ali A Moosavian ◽  
Alireza B Novinzadeh
Keyword(s):  
Flight Control ◽  
Formation Control ◽  
Degrees Of Freedom ◽  
Fuzzy Inference ◽  
Formation Flight ◽  
Innovative Strategy ◽  
Aerial Robots ◽  
Position Errors ◽  
Position Detection ◽  
Self Tuning

In this article, a novel guidance law derivation and new synchronization strategy are proposed for a virtual structure-based formation flight. These are designed using both aerodynamic and dynamics equations of aerial robots to facilitate implementation of the guidance and control laws. The guidance commands are derived in the form of acceleration based on a new analytical approach. These acceleration commands are converted to suitable inputs for the control system in the form of velocity, roll and pitch angles by employing an innovative strategy. In addition, a new synchronization strategy for virtual structure formation control is proposed. In this strategy, each agent utilizes the other agents’ actual position rather than their position errors. The proposed strategy is capable of shape formation flight using a passive sensor, such as vision sensors, for position detection of neighbour agents. This ability makes the proposed strategy more reliable than conventional synchronization methods. The mentioned strategy is further improved by self-tuning of the synchronization gain based on a fuzzy inference. The simulation of formation flight for a group of three fixed-wing aerial robots using six degrees of freedom models for each one reveals the merits of the proposed strategy. In fact, this approach significantly decreases the number of oscillations and corresponding amplitudes of position/orientation error for each agent. This is a crucial aspect of the mission performance for formation flight control.

Automatic Flight Control of Unmanned Helicopter Based on Nonlinear Model

2012 ◽  
Vol 472-475 ◽  
pp. 1492-1499
Author(s):  
Run Xia Guo
Keyword(s):  
Nonlinear Model ◽  
Flight Control ◽  
Attitude Control ◽  
Lyapunov Stability Theory ◽  
Test Results ◽  
Unmanned Helicopter ◽  
Control Laws ◽  
Control Approach ◽  
State Dependent ◽  
Compensation Technique

The Unmanned helicopter (UMH) movement was divided into two parts, namely, attitude and trajectory motion. And then a two-timescale nonlinear model was established. The paper improved and expanded state dependent riccati equation (SDRE) control approach, deriving analytical conditions for achieving global asymptotic stability with lyapunov stability theory. Proof was given. By combining improved SDRE control with nonlinear feed-forward compensation technique, the full envelop flight attitude control laws could be designed. On the basis of attitude control, trajectory controller was developed. Actual flight tests were carried out. Test results show that the control strategy is highly effective.

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