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To solve the problems of short battery life and low transportation safety of logistics drones, this paper aims to propose a design of logistics unmanned aerial vehicles (UAV) wing with a composite ducted rotor, which combines fixed wing and rotary-wing.

This UAV adopts tiltable ducted rotor combined with fixed wing, which has the characteristics of fast flight speed, large carrying capacity and long endurance. At the same time, it has the hovering and vertical take-off and landing capabilities of the rotary-wing UAV. In addition, aerodynamic simulation analysis of the composite model with a fixed wing and a ducted rotor was carried out, and the aerodynamic influence of the composite model on the UAV was analyzed under different speeds, fixed wing angles of attack and ducted rotor speeds.

The results were as follows: when the speed of the ducted rotor is 2,500 rpm, CL and K both reach maximum values. But when the speed exceeds 3,000 rpm, the lift will decrease; when the angle of attack of the fixed wing is 10° and the rotational speed of the ducted rotor is about 3,000 rpm, the aerodynamic characteristics of the wing are better.

The novelty of this work comes from a composite wing design of a fixed wing combined with a tiltable ducted rotor applied to the logistics UAVs, and the aerodynamic characteristics of the design wing are analyzed.

Dual-thrust hybrid unmanned aerial vehicle (UAV) technology offers a highly robust and efficient system that incorporates the take-off and landing capabilities of rotary-wing aircraft with the endurance capacities of fixed-wing aircraft. The purpose of this study is to model and control a hybrid UAV in three distinct flight modes: rotary-wing, fixed-wing and over-actuated model.

Model predictive control (MPC) along with linear models are applied to design controllers for the rotary-wing or vertical take-off and transition to the fixed-wing flight. The MPC algorithm is implemented with two approaches, first in its usual form and then in a new form with the help of tracking error variables as state variables.

Because the tracking error variables are more compatible with the cost function used in MPC, the results improve significantly. This is especially important for a safe and stable transition from rotary-wing to fixed-wing flight, which should be done quickly. The authors also propose a control allocation strategy with MPC algorithm to exploit the thrust and control inputs of both rotary-wing and fixed-wing systems for the transition phase. As the control system is over-actuated, the proposed algorithm distributes the control signal among the actuators better than the MPC alone. The numerical results show that the flight trajectory is also improved.

The research background is reviewed in the introduction section. The other sections are originally developed in this paper to the best of the authors’ knowledge.

This paper aims to overcome the main obstacle to compare the merits of the different control strategies for fixed-wing unmanned aerial vehicles (UAVs) to assess autopilot performances. Up to now, the published studies of control strategies have been carried out over disperse models, thus being complicated, if not impossible, to compare the merits of each proposal. The authors present a worked benchmark for autopilots studies, consisting of generalized models obtained by merging UAVs’ parameters gathered from selected literature (journals) with other parameters directly obtained by the authors to include some relevant UAVs whose models are not provided in the literature. To obtain them it has been used a dedicated software (from U.S. Air Force).

The proposed models have been constructed by averaging both the main aircraft defining parameters (model derivatives) and pole-zero locations of longitudinal transfer functions. The suitability of the used methodologies has been checked from their capability to fit the short period and the phugoid modes. Previous analytical model arrangement has been required to match a uniform set of parameters, as the inner state variables are neither the same along the different published models nor between the additional models the authors have here contributed. Besides, moving models between the space state representation and transfer function is not just a simple averaging process, as neither the parameters nor the model orders are the same in the different published works. So, the junction of the models to a common set of parameters requires some residual’s computation and transient responses assessment (even Fourier analysis has been included to preserve the dominance of the phugoid) to keep the main properties of the models. The least mean squares technique has been used to have better fittings between SISO model parameters with state–space ones.

Both the SISO (Laplace) and state-space models for the longitudinal transfer function of an “averaged” fixed-wing UAV are proposed.

More complicated situations, such as strong wind conditions, need another kind of models, usually based on finite element method simulation. These particular models apply fluid dynamics to study aerostructural aircraft aspects, such as flutter and other aerolastic aspects, the behavior under icing conditions or other distributed parameter problems. Even some models aim to control other aspects than the autopilot, such as the trajectory prediction. However, these models are not the most suitable for the basic UAV autopilot design (early design), so they are outside the objective of this paper. Obviously, the here-considered UAVs are not all the existing ones, but the number is large enough to consider the result as a reliable and realistic representation. The presented study may be seen as a stepping stone, allowing to include other UAVs in future works.

The proposed models can be used as benchmarks, or as a previous step to produce improved benchmarks, in order to have a common and realistic scenario the compare the benefits of the different control actions in UAV autopilots continuously presented in the published research.

A work with the scope of the presented one, merging model parameters from literature with other (often referred in papers and websites) whose parameters have been obtained by the authors has been never published.

The purpose of this paper is to develop a distributed and integrated method to get a fast and feasible solution for cooperative mission planning of multiple heterogeneous unmanned aerial vehicles (UAVs).

In this study, the planning process is conducted in a distributed framework; the cooperative mission planning problem is reformulated with some specific constraints in the real mission; a distributed genetic algorithm is the algorithm proposed for searching for the optimal solution; genes of the chromosome are modified to adapt to the heterogeneous characteristic of UAVs; a fixed-wing UAV’s six degrees-of-freedom (DOF) model with a path following method is used to test the proposed mission planning method.

This method not only has the ability to obtain good feasible solutions but also improves the operating rate vastly.

This study is only applied to the case where the communication among UAVs is linked during the mission.

This study is expected to be practical for a real mission because of its fast operating rate and good feasible solution.

This solution is tested on a fixed-wing UAV’s 6-DOF model by a path following method, so it is believable from the perspective of an autonomous UAV guidance and control system.

The purpose of the paper is to examine a fixed wing unmanned aerial vehicle (UAV) as it undergoes five flight scenarios under straight and level, level climb, level turn, climbing turn and level steady heading sideslip conditions in a desired and controlled manner using constrained multi input multi output (MIMO) model predictive controllers (MPCs).

An MPC strategy based on the lateral and longitudinal linear models is proposed for the flight control design. Simulations are carried out for the nonlinear closed-loop aircraft Simulink model available from the University of Minnesota UAV research group with the implemented MIMO MPCs designed in this paper.

The results of the simulations show that the MIMO MPCs can achieve satisfactory performance and flying qualities under three different test conditions in terms of existing unmeasured outputs and unmeasured output disturbances.

The MPCs designed in this paper can be implemented to UAVs. Therefore, the implementation is considered as an advanced research.

The proposed MPC design in this paper provides more flexibility in terms of tracking complex trajectories comparing with the classical controllers in the literature. Besides they provide to change more than one reference of the states at any time.

The purpose of this paper is to give reviews on the platform modeling and design of a controller for autonomous vertical take-off and landing (VTOL) tilt rotor hybrid unmanned aerial vehicles (UAVs). Nowadays, UAVs have experienced remarkable progress and can be classified into two main types, i.e. fixed-wing UAVs and VTOL UAVs. The mathematical model of tilt rotor UAV is time variant, multivariable and non-linear in nature. Solving and understanding these plant models is very complex. Developing a control algorithm to improve the performance and stability of a UAV is a challenging task.

This paper gives a thorough description on modeling of VTOL tilt rotor UAV from first principle theory. The review of the design of both linear and non-linear control algorithms are explained in detail. The robust flight controller for the six degrees of freedom UAV has been designed using H-infinity optimization with loop shaping under external wind and aerodynamic disturbances.

This review will act as a basis for the future work on modeling and control of VTOL tilt rotor UAV by the researchers. The development of self-guided and fully autonomous UAVs would result in reducing the risk to human life. Civil applications include inspection of rescue teams, terrain, coasts, border patrol buildings, police and pipelines. The simulation results show that the controller achieves robust stability, good adaptability and robust performance.

The review articles on quadrotors/quadcopters, hybrid UAVs can be found in many literature, but there are comparatively a lesser amount of review articles on the detailed description of VTOL Tilt rotor UAV. In this paper modeling, platform design and control algorithms for the tilt rotor are presented. A robust H-infinity loop shaping controller in the presence of disturbances is designed for VTOL UAV.

The purpose of this paper is to provide an overview of unmanned aerial vehicle (UAV) developments, types, the major functional components of UAV, challenges, and trends of UAVs, and among the various challenges, the authors are concentrating more on obstacle sensing methods. This also highlights the scope of on-board vision-based obstacle sensing for miniature UAVs.

The paper initially discusses the basic functional elements of UAV, then considers the different challenges faced by UAV designers. The authors have narrowed down the study on obstacle detection and sensing methods for autonomous operation.

Among the various existing obstacle sensing techniques, on-board vision-based obstacle detection has better scope in the future requirements of miniature UAVs to make it completely autonomous.

The paper gives original review points by doing a thorough literature survey on various obstacle sensing techniques used for UAVs.

This paper aims to present a vision-based method for determination of the position of a fixed-wing aircraft that is approaching a runway.

The method determines the location of an aircraft based on positions of precision approach path indicator lights and approach light system with sequenced flashing lights in the image captured by an on-board camera.

As the relation of the lighting systems to the touchdown area on the considered runway is known in advance, the detected lights, seen as glowing lines or highlighted areas, in the image can be mapped onto the real-world coordinates and then used to estimate the position of the aircraft. Furthermore, the colours of lights are detected and can be used as auxiliary information.

The presented method can be considered as a potential source of flight data for autonomous approach and for augmentation of manual approach.

In this paper, a feasibility study of this concept is presented and primarily validated.

This paper aims to develop a method for tuning the parameters of the active disturbance rejection controller (ADRC) for fixed-wing unmanned aerial vehicles (UAVs). The bald eagle search (BES) algorithm has been improved, and a cost function has been designed to enhance the optimization efficiency of ADRC parameters.

A six-degree-of-freedom nonlinear model for a fixed-wing UAV has been developed, and its attitude controller has been formulated using the active disturbance rejection control method. The parameters of the disturbance rejection controller have been fine-tuned using the collaborative mutual promotion bald eagle search (CMP-BES) algorithm. The pitch and roll controllers for the UAV have been individually optimized to obtain the most effective controller parameters.

Inspired by the salp swarm algorithm (SSA), the interaction among individual eagles has been incorporated into the CMP-BES algorithm, thereby enhancing the algorithm's exploration capability. The efficient and accurate optimization ability of the proposed algorithm has been demonstrated through comparative experiments with genetic algorithm, particle swarm optimization, Harris hawks optimization HHO, BES and modified bald eagle search algorithms. The algorithm's capability to solve complex optimization problems has been further proven by testing on the CEC2017 test function suite. A transitional function for fitness calculation has been introduced to accelerate the ability of the algorithm to find the optimal parameters for the ADRC controller. The tuned ADRC controller has been compared with the classical proportional-integral-derivative (PID) controller, with gust disturbances introduced to the UAV body axis. The results have shown that the tuned ADRC controller has faster response times and stronger disturbance rejection capabilities than the PID controller.

The proposed CMP-BES algorithm, combined with a fitness function composed of transition functions, can be used to optimize the ADRC controller parameters for fixed-wing UAVs more quickly and effectively. The tuned ADRC controller has exhibited excellent robustness and disturbance rejection capabilities.

The CMP-BES algorithm and transitional function have been proposed for the parameter optimization of the active disturbance rejection controller for fixed-wing UAVs.

This study aims to discuss the simultaneous longitudinal and lateral flight control of the octorotor, a rotary wing unmanned aerial vehicle (UAV), for the first time under the effect of morphing and to improve autonomous flight performance.

This study aims to design and control the octorotor flight control system with stochastic optimal tuning under morphnig effect. For this purpose, models of different arm lengths of the octorotor were drawn in the Solidworks program. The morphing was carried out by simultaneously lengthening or shortening the arm lengths of the octorotor. The morphing rate was estimated by using simultaneous perturbation stochastic approximation (SPSA). The stochastic gradient descent algorithm, which is frequently used in machine learning, was used to estimate the changing moments of inertia with the change of arm lengths. The proportional integral derivative (PID) controller has been preferred as an octorotor control algorithm because of its simplicity of structure. The PID gains required to control both longitudinal and lateral flight were also estimated with SPSA.

With SPSA, three longitudinal flight PID gains, three lateral flight PID gains and one morphing ratio were estimated. PID gains remained within the limits set for SPSA, giving satisfactory results. In addition, the cost index created was 93% successful. The gradient descent algorithm used for the moment of inertia estimation achieved the optimum result in 1,570 iterations. However, in the simulations made with the obtained data, longitudinal and lateral flight was successfully carried out.

Octorotor longitudinal and lateral flight control was performed quickly and effectively with the proposed method. In addition, the desired parameters were obtained with the optimization methods used, and the longitudinal and lateral flight of the octorotor was successfully carried out in the desired trajectory.