Robust fixed-time flight controller for a dual-system convertible UAV in the cruise mode

This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.

A Dual-Cluster-Head Based Medium Access Control for Large-Scale UAV Ad-Hoc Networks

Unmanned Aerial Vehicle(UAV)ad hoc network has achieved significant growth for its flexibility,extensibility,and high deployability in recent years.The application of clustering scheme for UAV ad hoc network is imperative to enhance the performance of throughput and energy efficiency.In conventional clustering scheme,a single cluster head(CH)is always assigned in each cluster.However,this method has some weaknesses such as overload and premature death of CH when the number of UAVs increased.In order to solve this problem,we propose a dual-cluster-head based medium access control(DCHMAC)scheme for large-scale UAV networks.In DCHMAC,two CHs are elected to manage resource allocation and data forwarding cooperatively.Specifically,two CHs work on different channels.One of CH is used for intra-cluster communication and the other one is for inter-cluster communication.A Markov chain model is developed to analyse the throughput of the network.Simulation result shows that compared with FM-MAC(flying ad hoc networks multi-channel MAC,FM-MAC),DCHMAC improves the throughput by approximately 20%~50%and prolongs the network lifetime by approximately 40%.

Intelligent PID Control Method for Quadrotor UAV with Serial Humanoid Intelligence

Quadrotor unmanned aerial vehicles(UAVs)are widely used in inspection,agriculture,express delivery,and other fields owing to their low cost and high flexibility.However,the current UAV control system has shortcomings such as poor control accuracy and weak anti-interference ability to a certain extent.To address the control problem of a four-rotor UAV,we propose a method to enhance the controller’s accuracy by considering underactuated dynamics,nonlinearities,and external disturbances.A mathematical model is constructed based on the flight principles of the quadrotor UAV.We develop a control algorithm that combines humanoid intelligence with a cascade Proportional-Integral-Derivative(PID)approach.This algorithm incorporates the rate of change of the error into the inputs of the cascade PID controller,uses both the error and its rate of change as characteristic variables of the UAV’s control system,and employs a hyperbolic tangent function to improve the outer-loop control.The result is a double closed-loop intelligent PID(DCLIPID)control algorithm.Through MATLAB numerical simulation tests,it is found that the DCLIPID algorithm reduces the rise time by 0.5 s and the number of oscillations by 2 times compared to the string PID algorithm when a unit step signal is used as input.A UAV flight test was designed for comparison with the serial PID algorithm,and it was found that when the UAV planned the trajectory autonomously,the errors in the X-,Y-,and Z-directions were reduced by 0.22,0.21,and 0.31 m,respectively.Under the interference environment of artificial wind about 3.6 m·s-1,the UAV hovering error in X-,Y-,and Z-directions are 0.24,0.42,and 0.27 m,respectively.The simulation and experimental results show that the control method of humanoid intelligence and cascade PID can improve the real-time,control accuracy and anti-interference ability of the UAV,and the method has a certain reference value for the research in the field of UAV control.

Two-layer formation-containment fault-tolerant control of fixed-wing UAV swarm for dynamic target tracking

This paper tackles the formation-containment control problem of fixed-wing unmanned aerial vehicle(UAV)swarm with model uncertainties for dynamic target tracking in three-dimensional space in the faulty case of UAVs’actuator and sensor.The fixed-wing UAV swarm under consideration is organized as a“multi-leader-multi-follower”structure,in which only several leaders can obtain the dynamic target information while others only receive the neighbors’information through the communication network.To simultaneously realize the formation,containment,and dynamic target tracking,a two-layer control framework is adopted to decouple the problem into two subproblems:reference trajectory generation and trajectory tracking.In the upper layer,a distributed finite-time estimator(DFTE)is proposed to generate each UAV’s reference trajectory in accordance with the control objective.Subsequently,a distributed composite robust fault-tolerant trajectory tracking controller is developed in the lower layer,where a novel adaptive extended super-twisting(AESTW)algorithm with a finite-time extended state observer(FTESO)is involved in solving the robust trajectory tracking control problem under model uncertainties,actuator,and sensor faults.The proposed controller simultaneously guarantees rapidness and enhances the system’s robustness with fewer chattering effects.Finally,corresponding simulations are carried out to demonstrate the effectiveness and competitiveness of the proposed two-layer fault-tolerant cooperative control scheme.

Constrained Moving Path Following Control for UAV With Robust Control Barrier Function

This paper studies the moving path following(MPF)problem for fixed-wing unmanned aerial vehicle(UAV)under output constraints and wind disturbances.The vehicle is required to converge to a reference path moving with respect to the inertial frame,while the path following error is not expected to violate the predefined boundaries.Differently from existing moving path following guidance laws,the proposed method removes complex geometric transformation by formulating the moving path following problem into a second-order time-varying control problem.A nominal moving path following guidance law is designed with disturbances and their derivatives estimated by high-order disturbance observers.To guarantee that the path following error will not exceed the prescribed bounds,a robust control barrier function is developed and incorporated into controller design with quadratic program based framework.The proposed method does not require the initial position of the UAV to be within predefined boundaries.And the safety margin concept makes error-constraint be respected even if in a noisy environment.The proposed guidance law is validated through numerical simulations of shipboard landing and hardware-in-theloop(HIL)experiments.

Nonlinear direct data-driven control for UAV formation flight system

This paper proposes the nonlinear direct data-driven control from theoretical analysis and practical engineering,i.e.,unmanned aerial vehicle(UAV)formation flight system.Firstly,from the theoretical point of view,consider one nonlinear closedloop system with a nonlinear plant and nonlinear feed-forward controller simultaneously.To avoid the complex identification process for that nonlinear plant,a nonlinear direct data-driven control strategy is proposed to design that nonlinear feed-forward controller only through the input-output measured data sequence directly,whose detailed explicit forms are model inverse method and approximated analysis method.Secondly,from the practical point of view,after reviewing the UAV formation flight system,nonlinear direct data-driven control is applied in designing the formation controller,so that the followers can track the leader’s desired trajectory during one small time instant only through solving one data fitting problem.Since most natural phenomena have nonlinear properties,the direct method must be the better one.Corresponding system identification and control algorithms are required to be proposed for those nonlinear systems,and the direct nonlinear controller design is the purpose of this paper.

A UAV-Assisted V2X Network Architecture with Separated Data Transmission and Network Control

With the explosive increasing number of connecting devices such as smart phones, vehicles,drones, and satellites in the wireless networks, how to manage and control such a huge number of networking nodes has become a great challenge. In this paper, we combine the advantages of centralized networks and distributed networks approaches for vehicular networks with the aid of Unmanned Aerial Vehicle(UAV), and propose a Center-controlled Multihop Wireless(CMW) networking scheme consisting of data transmission plane performed by vehicles and the network control plane implemented by the UAV.Besides, we jointly explore the advantages of Medium Access Control(MAC) protocols in the link layer and routing schemes in the network layer to facilitate the multi-hop data transmission for the ground vehicles.Particularly, the network control plane in the UAV can manage the whole network effectively via fully exploiting the acquired network topology information and traffic requests from each vehicle, and implements various kinds of control based on different traffic demands, which can enhance the networking flexibility and scalability significantly in vehicular networks.Simulation results validate the advantages of the proposed scheme compared with existing methods.

Control Effect of UAV Low Volume Spray Technology on Thrips and Tomato Spotted Wilt Virus in Tobacco Field

[Objectives]The paper was to explore the influence of unmanned aerial vehicle(UAV)low volume spray technology on the control effect of viruliferous thrips and tomato spotted wilt virus(TSWV)under different pesticide concentrations,and to explore the effective control nodes and methods of thrips and TSWV.[Methods]According to the occurrence characteristics of thrips and TSWV,the field control effects of 4 pesticides on thrips and TSWV were tested by UAV with the thrips number and disease index as indicators,following the principle of regional and periodic control trials.[Results]In the groups of UAV and artificial prevention and control,4 agents were used alternatively,including 1%emamectin benzoate ME,1.7%abamectin imidacloprid ME,5%emamectin benzoate WDG,and 30%pyriproxyfen dinotefuran SL.There was no significant difference in the control effect of thrips and TSWV among treatment 1(recommended dosage of UAV agent),treatment 2(reduction of recommended dosage of UAV agent by 25%)and treatment 4(recommended dosage of artificial control agent),and the control effects on thrips were more than 83.16%in the 3 treatments.The disease index of TSWV in the 3 treatments decreased from 8.64±1.37 in the blank control group to less than 3,which reached the prevention and control threshold.But treatment 3(reduction of recommended dosage of UAV agent by 50%)did not reach the prevention and control threshold.The disease index of TSWV in the blank control area increased with the increase of the number of live nymphs of thrips,and there was a significant positive correlation,with good fitness.[Conclusions]UAV has a significant impact on the control effect of thrips and TSWV under different pesticide concentrations.In the actual flight control application,it is recommended that the amount of the pesticides is about 3/4 and not less than 1/2 of that of the artificial application.The control area should be extended to 100 m of the ridge of the tobacco field,and UAV is used periodically to control thrips and TSWV for 5 times from pre-transplanting stage to pre-squaring stage of flue-cured tobacco.The control effect is significantly different from the traditional artificial application.

Functional Sustainability of a Flight Dynamics Control System for Stable Hovering Flight of an Unmanned Aerial Vehicle(UAV),such as in Agricultural Applications:Mathematical Modeling and Simulation

The simulation of a control system for the longitudinal axis of the rotary or fixed-wing unmanned aerial vehicles(UAVs)is demonstrated in this study.The control unit includes design considerations of two controllers to provide robust stability,tracking of the proposed linear dynamics,an adequate set of proportional-integral-derivative(PID)controller gains,and a minimal cost function.The PID control and linear quadratic regulator(LQR)with or without full-state-observer were evaluated.An optimal control system is assumed to provide fast rise and settling time,minimize overshoot,and eliminate the steady-state error.The effectiveness of this approach was verified by a linear model of the UAV aircraft in the semi-dynamic simulation platform of Matlab/Simulink,in which the open-loop system was assessed in terms of flight robustness and reference tracking.The experimental results show that the proposed controllers effectively improve the configuration of the control system of the plant,maintain the sustainability of the dynamic flight model stability,and diminish the flight controller errors.The LQR provides robust stability,but it is not optimal in the transient phase of particular plant output.The PID control system can adjust the controller’s gains for optimal hovering(or stable slow flight)and is especially useful for the tracking system.Finally,comparing aircraft stability using PID and LQR controllers shows that the latter has less overshoot and a shorter settling time;in addition,all proposed controllers can be practically deployed as one UAV’s system,which can be handled as an exemplary model of the UAV flight management system.

Multi-UAV cooperative maneuver decision-making for pursuitevasion using improved MADRL

Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.

Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

Observer-based backstepping longitudinal control for carrier-based UAV with actuator faults

The paper presents the longitudinal control for the carrier-based unmanned aerial vehicle (UAV) system with unmeasured states, actuator faults, control input constraints, and external disturbances. By combining output state observer, adaptive fuzzy control, and constraint backstepping technology, a robust fault tolerant control approach is proposed. An output state observer with fuzzy logic systems is developed to estimate unmeasured states, and command filters rather than differentiations of virtual control law are used to solve the computational complexity problem in traditional backstepping. Additionally, a robust term is introduced to offset the fuzzy adaptive estimation error and external disturbance, and an appropriate fault controller structure with matching conditions obtained from fault compensation is proposed. Based on the Lyapunov theory, the designed control program is illustrated to guarantee that all the closed-loop signals of the given system are bounded, and the output errors converge to a small neighborhood of zero. A carrier-based UAV nonlinear longitudinal model is employed to testify the feasibility and validity of the control scheme. The simulation results show that all the controllers can perform at a satisfactory level of reference tracking despite the existence of unknown aerodynamic parameters and actuator faults. © 2017 Beijing Institute of Aerospace Information.

A Software-in-the-Loop Implementation of Adaptive Formation Control for Fixed-Wing UAVs

This paper discusses the design and software-in-theloop implementation of adaptive formation controllers for fixedwing unmanned aerial vehicles(UAVs) with parametric uncertainty in their structure, namely uncertain mass and inertia. In fact, when aiming at autonomous flight, such parameters cannot assumed to be known as they might vary during the mission(e.g.depending on the payload). Modeling and autopilot design for such autonomous fixed-wing UAVs are presented. The modeling is implemented in Matlab, while the autopilot is based on ArduPilot, a popular open-source autopilot suite. Specifically, the ArduP ilot functionalities are emulated in Matlab according to the Ardupilot documentation and code, which allows us to perform software-in-the-loop simulations of teams of UAVs embedded with actual autopilot protocols. An overview of realtime path planning, trajectory tracking and formation control resulting from the proposed platform is given. The software-inthe-loop simulations show the capability of achieving different UAV formations while handling uncertain mass and inertia.

Tradeoff Analysis of Factors Affecting Longitudinal Carrier Landing Performance for Small UAV Based on Backstepping Controller

Tradeoff analysis of the factors,including external environment and unmanned aerial vehicle(UAV)aerodynamic attributes,which affect longitudinal carrier landing performance,is important for small UAV.First,small UAV longitudinal carrier landing system is established,as well as the nonlinear dynamics and kinematics model,and then the longitudinal flight control system using backstepping technology with minimum information about the aerodynamic is designed.To assess the landing performance,a variety of influencing factors are considered,resulting in the constraints of aerodynamic attributes of carrier UAV.The simulation results show that the severe sea condition has the greatest influence on landing dispersion,while air wake is the primary factor on impact velocity.Among the longitudinal aerodynamic parameters,the lift curve slope is the most important factor affecting the landing performance,and increasing lift curve slope can improve the landing performance significantly.A better system performance will be achieved when the lift curve slope is larger than 2per radian.

Robust Tracking Control of Uncertain MIMO Nonlinear Systems with Application to UAVs

In this paper, we consider the robust adaptive tracking control of uncertain multi-input and multi-output (MIMO) nonlinear systems with input saturation and unknown external disturbance. The nonlinear disturbance observer (NDO) is employed to tackle the system uncertainty as well as the external disturbance. To handle the input saturation, an auxiliary system is constructed as a saturation compensator. By using the backstepping technique and the dynamic surface method, a robust adaptive tracking control scheme is developed. The closed-loop system is proved to be uniformly ultimately bounded thorough Lyapunov stability analysis. Simulation results with application to an unmanned aerial vehicle (UAV) demonstrate the effectiveness of the proposed robust control scheme. © 2014 Chinese Association of Automation.

A Trajectory Prediction Based Intelligent Handover Control Method in UAV Cellular Networks

The airborne base station(ABS) can provide wireless coverage to the ground in unmanned aerial vehicle(UAV) cellular networks.When mobile users move among adjacent ABSs,the measurement information reported by a single mobile user is used to trigger the handover mechanism.This handover mechanism lacks the consideration of movement state of mobile users and the location relationship between mobile users,which may lead to handover misjudgments and even communication interrupts.In this paper,we propose an intelligent handover control method in UAV cellular networks.Firstly,we introduce a deep learning model to predict the user trajectories.This prediction model learns the movement behavior of mobile users from the measurement information and analyzes the positional relations between mobile users such as avoiding collision and accommodating fellow pedestrians.Secondly,we propose a handover decision method,which can calculate the users' corresponding receiving power based on the predicted location and the characteristic of air-to-ground channel,to make handover decisions accurately.Finally,we use realistic data sets with thousands of non-linear trajectories to verify the basic functions and performance of our proposed intelligent handover controlmethod.The simulation results show that the handover success rate of the proposed method is 8% higher than existing methods.

Quadcopter UAV Modeling and Automatic Flight Control Design

The mathematical model of quadcopter-unmanned aerial vehicle （UAV） is derived by using two approaches： One is the Newton-Euler approach which is formulated using classical meehanics; and other is the Euler-Lagrange approach which describes the model in terms of kinetic （translational and rotational） and potential energy. The proposed quadcopter＇s non-linear model is incorporated with aero-dynamical forces generated by air resistance, which helps aircraft to exhibits more realistic behavior while hovering. Based on the obtained model, the suitable control strategy is developed, under which two effective flight control systems are developed. Each control system is created by cascading the proportional-derivative （PD） and T-S fuzzy controllers that are equipped with six and twelve feedback signals individually respectively to ensure better tracking, stabilization, and response. Both pro- posed flight control designs are then implemented with the quadcopter model respectively and multitudinous simulations are conducted using MATLAB/Simulink to analyze the tracking performance of the quadcopter model at various reference inputs and trajectories.

PID-type fault-tolerant prescribed performance control of fixed-wing UAV

This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.

Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural networks.Thus,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations directly.The network training is performed offline,which requires low computational power.The target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation algorithm.Such a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small size.We compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the aircraft.It was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve that.The allocation error was also determined in both cases.Furthermore,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

Dynamic affine formation control of networked under-actuated quad-rotor UAVs with three-dimensional patterns

This paper focuses on the solution to the dynamic affine formation control problem for multiple networked underactuated quad-rotor unmanned aerial vehicles(UAVs)to achieve a configuration that preserves collinearity and ratios of distances for a target configuration.In particular,it is investigated that the quad-rotor UAVs are steered to track a reference linear velocity while maintaining a desired three-dimensional target formation.Firstly,by integrating the properties of the affine transformation and the stress matrix,the design of the target formation is convenient and applicable for various three-dimensional geometric patterns.Secondly,a distributed control method is proposed under a hierarchical framework.By introducing an intermediary control input for each quad-rotor UAV in the position loop,the necessary thrust input and the desired attitude are extracted.In the attitude loop,the desired attitude represented by the unit quaternion is tracked by the designed torque input.Both conditions of linear velocity unavailability and mutual collision avoidance are also tackled.In terms of Lyapunov theory,it is prooved that the overall closed-loop error system is asymptotically stable.Finally,two illustrative examples are simulated to validate the effectiveness of the proposed theoretical results.