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Modern aviation technology development heavily relies on computer simulations. SIL (Software-In-The-Loop) simulations are essential for evaluating autopilots and control algorithms for multi-rotors, including drones and other UAVs (Unmanned Aerial Vehicle). In such simulations, it is possible to compare the flight parameters achieved by flying platforms using various commercial autopilots widely used in the UAV sector. This research aims to provide objective and comprehensive insights into the effectiveness of different autopilot systems This article examines the simulated flight test results of a drone performing the same mission using different autopilot systems. The X-Plane software was used as an environment to simulate the dynamics of the drone and its surroundings. Matlab/Simulink r2023a provided the interface between autopilot software and X-Plane models. Those methods allowed us to obtain an appropriate comparison of the autopilot systems and indicate the main differences between them. This research focused on analyzing UAV flight characteristics such as stability, trajectory tracking, response time to control changes, and the overall effectiveness of autopilots. Various flight scenarios including take-off, landing, flight at a constant altitude, dynamic manoeuvrers and, flight along a planned trajectory were also examined. In order to obtain the most accurate and realistic results, the tests were carried out in various weather conditions. The aim of this research is to provide objective data and analysis to compare the performance of commercial autopilots. This method offers several advantages, including cost-effective testing, the ability to test in diverse environmental conditions, and the evaluation of autopilot algorithms without the need for real hardware. The findings of this study may have a considerable impact on how autopilot designers and developers choose the best platforms and technologies for their projects. Future research on this topic will compare the obtained data with flight test data.

The exploitation of offshore wind energy by means of floating wind turbines is gaining traction as a suitable option to produce sustainable energy. Multi‐rotor floating wind turbines have been proposed as an appealing option to reduce the costs associated with manufacturing, logistics, offshore installations, and operation and maintenance of large wind turbine components. The development of such systems is forestalled by the lack of a dedicated tool for dynamics and load analysis. Standard codes, such as FAST by NREL, offer the desired fidelity level but are not able to accommodate multi‐rotor configurations. A few experimental codes have been also proposed, which may accommodate multi‐rotor systems, but low flexibility makes them impractical to study a vast range of innovative multi‐rotor FWTs concepts. To close the gap, this work presents the development and comprehensive benchmark of a fully coupled aero‐hydro‐servo‐elastic tool able to easily accommodate arbitrary platform and tower geometries and the number of wind turbines employed. Development is carried out in Modelica, which allows for the employment of the same code functionality in a virtually unlimited number of physical configurations. Full blade‐element momentum capabilities are achieved by integrating into Modelica the well‐established NREL aerodynamic module AeroDyn v15 within FAST v8. Structural dynamics of tower and blades are implemented through a lumped‐element approach. Hydrodynamic loads are computed by employing the DNV software SESAM WADAM. Thorough benchmark is performed against FAST, and positive results are obtained. The dynamic performance of a two‐rotor floating wind turbine is finally assessed considering different turbulence spectrums.

A multi‐rotor wind turbine (MRWT) is a concept that can reduce the size of the rotor blades compared to a single‐rotor wind turbine (SRWT). Making a cost‐optimized MRWT requires a detailed understanding of its stability properties. This paper aims to establish a physical and intuitive representation of whirling modes for three‐bladed isotropic SRWT and MRWT. An aeroelastic simulation of a nonlinear SRWT model is presented to empathize the importance of whirling. The whirling concept is introduced by simplifying the complexity of the wind turbine rotor into two models. From the models, edgewise and flapwise whirling modes are analyzed. An analytical model of a two‐rotor wind turbine is examined to present the edgewise whirling modes of MRWT. The flapwise whirling modes for MRWT are introduced by using results from edgewise whirling and findings from previous research. The MRWT whirling analysis shows whirling from multiple rotors creates reaction forces to the supporting structure when the rotors have the same speed. This results in whirling coupling modes at the same natural frequency. One is a rotor symmetric whirling mode where the rotors whirling are in phase and a rotor asymmetric mode where whirling of the rotors are out of phase. The whirling coupling effects are minimized in the case that the rotors have different speeds.

In this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented rotors which simultaneously addresses the local reference trajectory planning and tracking problems. This work brings into question some common modeling and control design choices that are typically adopted to guarantee robustness and reliability but which may severely limit the attainable performance. Unlike most of state of the art works, the proposed method takes advantages of a unified nonlinear model which aims to describe the whole robot dynamics by explicitly including a realistic physical description of the actuator dynamics and limitations. As a matter of fact, our solution does not resort to common simplifications such as: (1) linear model approximation, (2) cascaded control paradigm used to decouple the translational and the rotational dynamics of the rigid body, (3) use of low-level reactive trackers for the stabilization of the internal loop, and (4) unconstrained optimization resolution or use of fictitious constraints. More in detail, we consider as control inputs the derivatives of the propeller forces and propose a novel method to suitably identify the actuator limitations by leveraging experimental data. Differently from previous approaches, the constraints of the optimization problem are defined only by the real physics of the actuators, avoiding conservative – and often not physical – input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is implemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The performances of the control system are finally validated by means of real-time simulations and in real experiments, with a large spectrum of heterogeneous multi-rotor systems: an under-actuated quadrotor, a fully-actuated hexarotor, a multi-rotor with orientable propellers, and a multi-rotor with an unexpected rotor failure . To the best of our knowledge, this is the first time that a predictive controller framework with all the valuable aforementioned features is presented and extensively validated in real-time experiments and simulations.

The advent and evolution of Unmanned Aerial Vehicles (UAVs) and photogrammetric techniques has provided the possibility for on-demand high-resolution environmental mapping. Orthoimages and three dimensional products such as Digital Surface Models (DSMs) are derived from the UAV imagery which is amongst the most important spatial information tools for environmental planning. The two main types of UAVs in the commercial market are fixed-wing and multi-rotor. Both have their advantages and disadvantages including their suitability for certain applications. Fixed-wing UAVs normally have longer flight endurance capabilities while multi-rotors can provide for stable image capturing and easy vertical take-off and landing. Therefore, the objective of this study is to assess the performance of a fixed-wing versus a multi-rotor UAV for environmental mapping applications by conducting a specific case study. The aerial mapping of the Cors-Air model aircraft field which includes a wetland ecosystem was undertaken on the same day with a Skywalker fixed-wing UAV and a Raven X8 multi-rotor UAV equipped with similar sensor specifications (digital RGB camera) under the same weather conditions. We compared the derived datasets by applying the DTMs for basic environmental mapping purposes such as slope and contour mapping including utilising the orthoimages for identification of anthropogenic disturbances. The ground spatial resolution obtained was slightly higher for the multi-rotor probably due to a slower flight speed and more images. The results in terms of the overall precision of the data was noticeably less accurate for the fixed-wing. In contrast, orthoimages derived from the two systems showed small variations. The multi-rotor imagery provided better representation of vegetation although the fixed-wing data was sufficient for the identification of environmental factors such as anthropogenic disturbances. Differences were observed utilising the respective DTMs for the mapping of the wetland slope and contour mapping including the representation of hydrological features within the wetland. Factors such as cost, maintenance and flight time is in favour of the Skywalker fixed-wing. The multi-rotor on the other hand is more favourable in terms of data accuracy including for precision environmental planning purposes although the quality of the data of the fixed-wing is satisfactory for most environmental mapping applications.

An airborne anemometer, which monitors wind on the basis of Meteorological Multi-rotor UAVs (Unmanned Aerial Vehicles), is important for the prevention of catastrophe. However, its performance will be affected by the self-excited air turbulence generated by UAV rotors. In this paper, for the purpose of the correction of an error, we developed a method for the elimination of the influence of air turbulence on wind speed measurement. The corresponding correction model is obtained according to the CFD (Computational Fluid Dynamics) simulation of a six-rotor UAV which is carried out with the sliding grid method and the S-A turbulence model. Then, the model is applied to the developed prototype by adding the angle of attack compensation model of the airborne anemometer. It is shown by the actual application that the airborne anemometer can maintain the original measurement accuracy at different ascent speeds.

This paper proposes a novel methodology based on two intelligent algorithms for regulating the power output of a multi-rotor turbine system. A proportional-integral plus second-order integral regulator is utilized to regulate the energy output of an induction generator. The designed controller is characterized by its ease of configuration, cost-effectiveness, high robustness, and ease of implementation. The controller’s parameters are tuned using a genetic algorithm (GA) and a rooted tree optimization (RTO) algorithm, with the objective of maximizing operational performance and power quality. In accordance with the proposed design methodology, the optimal values for the parameters of the designed strategy are attained through the implementation of integral time-weighted absolute error (ITAE). The present controller has been designed to deviate from conventional controllers, and a comparison will be made between the two using MATLAB under various operating conditions. The operational performance was evaluated in comparison to the conventional algorithm in terms of current quality, torque ripples, threshold overshoot, system parameter changes, and so forth. The experimental results, as measured by the tests conducted, demonstrated that the proposed RTO-based regulator exhibited enhancements of up to 89.88% (traditional control) and 51.92% (GA) in active power ripples, 68.19% (compared to traditional control) in ITAE, 51.91% (traditional control) in reactive power overshoot, and 0.5% (compared to GA) in active power response time. Conversely, the proposed GA-based regulator yielded a steady-state error value that was 96.55% superior to the traditional approach and 86.48% more accurate than the RTO algorithm. Moreover, the efficacy of the RTO-based control system was found to be considerably augmented under variable system parameters. Total harmonic distortion improvements of 69% were observed compared to traditional control methods, and 1% compared to the GA technique. The findings of this study offer significant insights into enhancing the robustness of multi-rotor turbine systems and improving power quality.

It is of great significance to detect drones in airspace due to the substantial increase and regrettable misuse in the consumer market. In this paper, we establish a micro-motion theoretical model of a drone and analyze the micro-Doppler signature of rotor targets and the flicker mechanisms of the multi-rotor targets. Hence, for the target recognition problem of multi-rotor drones, a multi-rotor target micro-Doppler parameter estimation method is proposed. Firstly, a signal frequency domain segmentation method is proposed based on the complex variational mode decomposition (CVMD) to separate the high-frequency part of the high-frequency flicker in the frequency domain. Secondly, for the signal after frequency domain segmentation, a flicker time domain position method based on singular value decomposition (SVD) is proposed. Finally, by integrating CVMD frequency domain segmentation and SVD time domain positioning, the reconstruction of multi-rotor target scintillation at different speeds is realized, and the micro-motion parameters of rotor blades are successfully estimated. The simulation results show that the method has high accuracy in estimating the micro-motion parameters of a multi-rotor, which makes up for the shortage of the traditional method in estimating the micro-motion parameters of the multi-rotor target.

A diffuser-augmented wind turbine (DAWT) achieves greater power generation efficiency by increasing wind speed through the diffuser. Nevertheless, scaling up this technology is difficult because of the considerable amount of wind drag on the diffusers. To overcome this difficulty, a multi-rotor system with two or more wind turbines on the same structure is one approach to increasing wind turbine power output. This research proposes a computational fluid dynamics (CFD) method to evaluate the hydrodynamic performance of a large-scale multi-rotor system of DAWTs. Compared to conventional wind turbines, CFD simulations of DAWTs necessitate higher computational costs because of the need of high-resolution meshes for the diffuser. Furthermore, the computational cost of a multi-rotor system increases with the number of rotors. To address the issue of high computational cost, we use the Lattice Boltzmann Method (LBM), which is well suited to large-scale CFD simulations. A wind turbine is modeled as an actuator line model and a diffuser as a wall boundary. An adaptive mesh refinement approach generates higher resolution meshes near the rotor and diffuser. LBM simulations were conducted for a single DAWT and a multi-rotor system with five DAWTs. The LBM results of the wake velocity and pressure distributions were in agreement with those obtained from wind tunnel experiments and general CFD methods in earlier studies. To investigate the diffuser gap effects, we simulated five DAWTs with diffuser gaps of 5%–25% of the diffuser diameter. The power gain of each DAWT was assessed. Great performance improvements were found with diffuser gaps of 20% and 25% of the diffuser diameter. On average, the five DAWTs achieved a power gain of more than 10%. These findings confirmed the accurate evaluation capability of the proposed CFD method for hydrodynamic characteristics of multi-rotor systems using DAWTs.

To control the flight of the compound multi-rotor UAV which is a combination of coaxial rotor and quad-rotor, the attitude control method is proposed. The nonlinear attitude control dynamic model of the compound multi-rotor UAV is given. The Proportion-Proportion Integration Differentiation (P-PID) control method is used for the attitude control module and obtaining the virtual control values. The control values distribution matrix is used to realize mapping between the virtual control values and the multi-actuator. The rotation rate-blade pitch integration control method is used to coordinate the rotor’s rotation rate and blade pitch, which ensure fast response of the UAV’s attitude stabilization control. Simulation results show that the attitude controller can realize the UAV’s pitch, roll, yaw attitude motion control, and do well in attitude angle stability control when periodic change attitude angles is tracked.