Complex Aerodynamics Research Articles

Addressing VAWT Aerodynamic Challenges as the Key to Unlocking Their Potential in the Wind Energy Sector

While the wind turbine industry has been primarily dominated by horizontal-axis wind turbines, the forefront of knowledge of these turbines has revealed significant challenges in various aspects, including manufacturing, structural design, cost, and maintenance. On the other hand, the advantages associated with Darrieus vertical-axis wind turbines (VAWTs) demonstrate significant potential that can address the existing challenges of the wind turbine industry. Current work aims to investigate the practicality of this potential for the wind energy sector. To this end, the benefits of employing Darrieus turbines for domestic and industrial applications, isolated operation, and on/offshore windfarm applications have been explored. It is apparent that Darrieus VAWTs are better suited to a wide range of environments, whether they are deployed in isolation or integrated systems, and whether they are utilized on a small or large scale. Darrieus VAWTs are adaptable to urban unsteady variable wind, are less expensive on large scales, provide higher power density at the windfarm level, and provide stability for offshore platforms. Nevertheless, challenges remain in fully harnessing VAWT potential rooted in their complex aerodynamics. This serves as a primary challenge for VAWTs to address the challenges of the wind turbine industry in line with the 2050 roadmap.

Fuzzy-based collective pitch control for wind turbine via deep reinforcement learning

Wind turbines (WTs) have highly nonlinear and uncertain dynamics due to aerodynamic complexity, mechanical factors, and fluctuations in wind conditions. Turbulence and wind shear add complexity to modelling, especially in constant power region (region 3). Thus, an effective control design demands a deep understanding of the nonlinearities and uncertainties. This paper suggests a novel model-free reinforcement learning (RL) collective pitch angle controller to operate efficiently in region 3. The proposed controller stabilizes generator speed, maximizes power output, and minimizes fluctuations while accommodating system uncertainties, nonlinearity, and pitch limits. The disparity between WT dynamics due to wind speed perturbations and uncertainties is measured using a gap-metric criterion. The controller design adopts a deep deterministic policy gradient (DDPG) algorithm to train six agents in a medium-fidelity WT environment at different mean wind speeds to ensure the controller's robustness. Initially, imitation learning is used for efficient sample collection to fasten training convergence. Afterwards, the agent learns by interacting with the environment. After the training, the pitch control outputs from multi-trained agents are processed by a fuzzy system to have smooth transitions under different operating conditions. The resulting fuzzy DDPG (F-DDPG) controller is deployed to obtain the optimal pitch control action. The performance of the proposed F-DDPG controller is compared to the gain-scheduled PI (GSPI), Linear-Quadratic-Regulator (LQR), and single-DDPG-agent controllers. The controllers are simulated in high-fidelity onshore and offshore 5-MW WT environments using the OpenFAST/MATLAB simulation tools. The results reveal the superiority of the proposed controller in generalizing its optimal performance in different operating conditions.

An experimental study on the aerodynamic loads of a floating offshore wind turbine under imposed motions

Abstract. The rotor of a floating wind turbine is subject to complex aerodynamics due to changes in relative wind speeds at the blades and potential local interactions between blade sections and the rotor near wake. These complex interactions are not yet fully understood. Lab-scale experiments are highly relevant for capturing these phenomena and provide means for the validation of numerical design tools. This paper presents a new wind tunnel experimental setup able to study the aerodynamic response of a wind turbine rotor when subjected to prescribed motions. The present study uses a 1:148 scale model of the DTU 10 MW reference wind turbine mounted on top of a 6 degrees of freedom parallel kinematic robotic platform. Firstly, the thrust variation of the turbine is investigated when single degree of freedom harmonic motions are imposed by the platform, with surge, pitch and yaw being considered in this study. For reduced frequencies greater than 1.2, it is found that the thrust variation is amplified by up to 150 % compared to the quasi-steady value when the turbine is subject to pitch and surge motions, regardless of the amplitude of motion. A similar behaviour is also noticed under yaw motions. Secondly, realistic 6 degrees of freedom motions are imposed by the platform. The motions are derived from FAST simulations performed on the full-scale turbine coupled with the TripleSpar floater, and the tests aim at exploring the thrust force dynamics for different sea states and wind conditions, obtaining reasonable agreement with the simulations. Finally, the work shows the capabilities of an off-the-shelf hexapod to conduct hybrid testing of floating offshore wind turbines in wind tunnels, as well as its limitations in performing such tests.

Reduction of rotorcraft BVI using synthetic jets; computational studies using LES

In rotorcraft, the blade-vortex interaction (BVI) has been recognized as one of the main sources of noise and vibrations, affecting its aerodynamics performance and stability. Active and passive flow control techniques, for the reduction of BVI, have been investigated. The passive flow control techniques have proved to be inefficient due to the complex aerodynamics of rotorcraft. Thus, active flow control techniques has become of particular interest. In the present research we propose a novel approach, for the reduction of rotorcraft’s noise and vibrations due to BVI. The main idea of this approach is to inject air at the leading-edge of the blade to alter the characteristics (strength and core size) of the incoming vortex and thus, minimize the noise and vibrations associated with BVI. Computational studies are carried out using the large-eddy simulation (LES) with the dynamic Smagorisky sub-grid scale model. The computations are carried out for a flow of Reynolds number R e = 1.3 × 10 6 , based on the chord of NACA0012 airfoil and free-stream velocity. The studies show that injecting air at the leading edge of the blade, the influence of blade-vortex interaction on the aerodynamic coefficients is significantly reduced. Higher reduction of BVI effect, on the aerodynamic coefficients, was achieved with the increase of the speed of the synthetic jet. The reduction of the BVI, also, leads to the reduction of the vibrations.

An Optimal Wind Farm Operation Strategy for the Provision of Frequency Containment Reserve Incorporating Active Wake Control

This study proposes a novel operation strategy for wind farms' optimal Frequency Containment Reserve (FCR) provision that simultaneously distributes FCR and optimally controls wake formation. The power reserve allocation is dynamically decided at the wind farm supervisory control level, considering the intermittent wind power and direction, grid frequency stochasticity, and the aerodynamic complexity of the wake. A two-stage stochastic programming approach supports decision-making for an optimal contribution to day-ahead energy/FCR markets considering sub-hourly wind power and grid frequency uncertainty. Moreover, a novel method is used to reduce the computational complexity by employing a data-driven surrogate model of wake formation in the optimizer. This surrogate model consists of a neural network trained on the Gauss-Curl-Hybrid wake model in FLORIS. This deep learning approach allows fast estimation of the wake control parameters, i.e., the optimal yaw angles and axial induction factors. Then, a coevolutionary-based multi-objective particle swarm optimization searches for the optimal deloading of the WTs and maximizes the total power production and kinetic energy while minimizing wake. The performance of the proposed algorithm is evaluated on the C-Power wind farm layout in the North Sea. Simulation results demonstrate its effectiveness in improving the wind farm's overall performance for different operational conditions.

Multi‐fidelity data fusion through parameter space reduction with applications to automotive engineering

AbstractMulti‐fidelity models are of great importance due to their capability of fusing information coming from different numerical simulations, surrogates, and sensors. We focus on the approximation of high‐dimensional scalar functions with low intrinsic dimensionality. By introducing a low dimensional bias we can fight the curse of dimensionality affecting these quantities of interest, especially for many‐query applications. We seek a gradient‐based reduction of the parameter space through linear active subspaces or a nonlinear transformation of the input space. Then we build a low‐fidelity response surface based on such reduction, thus enabling nonlinear autoregressive multi‐fidelity Gaussian process regression without the need of running new simulations with simplified physical models. This has a great potential in the data scarcity regime affecting many engineering applications. In this work we present a new multi‐fidelity approach that involves active subspaces and the nonlinear level‐set learning method, starting from the preliminary analysis previously conducted (Romor F, Tezzele M, Rozza G. Proceedings in Applied Mathematics & Mechanics. Wiley Online Library; 2021). The proposed framework is tested on two high‐dimensional benchmark functions, and on a more complex car aerodynamics problem. We show how a low intrinsic dimensionality bias can increase the accuracy of Gaussian process response surfaces.

Attitude Control of Quadrotor UAV Using Improved Active Disturbance Rejection Control

The quadrotor UAV has complex aerodynamics, unstable altitude, and easy to be disturbed by internal and external uncertainties during flight, so good attitude control becomes a challenge, this paper improves the active disturbance rejection controller to improve the system's anti-jamming ability and response speed in response to the above problems. Firstly, a quadrotor UAV dynamics model is established; then the Ifal function is constructed, which solves the problems that the inflection point of the fal function is not smooth, which is easy to cause the system jitter and the system gain is large when the error is large, and finally the performance is verified by using MATLAB/Simulink simulation software. The simulation results show that the constructed Ifal function is smoother and has better convergence, and compared with the traditional active disturbance rejection control, the improved active disturbance rejection control system has faster response speed, stronger anti-jamming ability and robustness in the attitude control of quadrotor UAV.

Wind Tunnel Study of a Grid Fin Stabilized Guided Projectile

There is a need for methods/techniques to analyze the aerodynamics of grid fins at high angle of attack. The existing methods to predict or compute the aerodynamic parameters for grid fins are inadequate at high angles of attack. The present study attempts to extend the understanding of the complex aerodynamics associated with grid fins. The analysis draws its conclusion from wind tunnel test results of five basic grid fin configurations. A vortex lattice solution was used to model the aerodynamics of the chosen grid fins. Next the analytical and empirical relations as discussed in open literature were applied to model grid fin aerodynamics at high angle of attack. The aerodynamic coefficients were computed. These coefficients were then compared with the experimental results obtained using the five grid fin configurations. To improve the matching at high angle of attack a proposed approach using Kirchoff’s theory along with vortex lattice method was applied. The results show that this approach can be a starting tool to model lattice/grid fin aerodynamics.

Mimicking the Mechanism of Lift Generation in Dragonflies

Human pursuit of flight has learnt many lessons from nature and a few adaptations have led to phenomenal progress. Insect flight uses complex unsteady aerodynamics to generate lift in addition to producing thrust. A close look at the dragonfly provides some clues to mimic its flight using passive means by separating propulsion and lifting mechanisms. Though the dragonfly can independently flap each of its wings to generate lift and thrust, during forward flight, fore-wings alone flap while the aft-wings remain nearly steady. We adopt this as basis for new passive configurations to generate steady lift. Conceptually, we replace fore-wings with a cylinder that is known to shed vortices, to mimic flapping. A simple plate replaces the aft-wings. Flow analysis of such a configuration at Reynolds Number of 7500 revealed a steady flow topology featuring a trapped vortex over the plate, resulting in steady lift to drag ratio of 3. A further optimized configuration consisting of a semi-circular cylinder upstream and a cambered plate downstream resulted in lift to drag ratio of 14.5, which is considerable for these flow regimes, opening up new possibilities for design of nano-flight vehicles.

Encoding nonlinear and unsteady aerodynamics of limit cycle oscillations using nonlinear sparse Bayesian learning

This article investigates the applicability of a recently proposed, nonlinear sparse Bayesian learning (NSBL) algorithm to identify and estimate the complex aerodynamics of limit cycle oscillations. NSBL provides a semi-analytical framework for determining the data-optimal sparse model nested within a (potentially) over-parameterized model. This is particularly relevant to nonlinear dynamical systems where modelling approaches involve the use of physics-based and data-driven components. In such cases, the data-driven components, where analytical descriptions of the physical processes are not readily available, are often prone to overfitting, meaning that the empirical aspects of these models will often involve the calibration of an unnecessarily large number of parameters. While an overparameterized model may fit the observed data well, such models may be inadequate for making predictions in regimes that are different from those wherein the data were recorded. In view of this, it is desirable to not only calibrate the model parameters, but also identify the optimal compromise between data fit and model complexity. In this article, we exhibit the optimal model discovery for an aeroelastic system wherein the structural dynamics are well-known and described by a differential equation model, coupled with a semi-empirical aerodynamic model for laminar separation flutter, resulting in low-amplitude limit cycle oscillations (LCO). To illustrate the performance of the algorithm, in this article, we use synthetic data and demonstrate the ability of the algorithm to correctly rediscover the optimal model and model parameters, given a known data-generating model. The synthetic data are generated from a forward simulation of a known differential equation model with parameters selected so as to mimic the dynamics observed in wind-tunnel experiments. Subsequently, we demonstrate the performance of the algorithm for model selection using noisy LCO data from wind tunnel experiments. As there is no ground truth available for the experimental data case, we provide a comparison between NSBL and Bayesian model selection to validate the results, and demonstrate the use of NSBL as an efficient alternative to traditional methods.

Three Rotor Hub Flow Prediction Workshops (2016–2020): What Did We Learn and What's Next?

The 'Rotor Hub Flow Prediction Workshops' have been productive collaborations between experimental and computational efforts in the important area of high-Reynolds number model testing of rotor hubs and associated complex interactional aerodynamics in the long-age wake as relevant to current and future rotorcraft. As such the hub flow workshops have joined the ranks of past successful collaborations such as the UH-60 Airloads and HART-II workshops. This paper begins by describing the basic physics of rotor hub flows and gives a brief summary of recent water-tunnel test campaigns. Following, the evolution of the hub flow workshops is summarized, with emphasis on the productive interactions between experimentalists and computational participants. A compilation of computational blind comparison results against measured data for all three workshops thus far is presented. Challenges associated with uncertainties in both experiments and computations and their effect on quantitative comparisons are discussed. In particular, emphasis is given to the "lessons learned" on both sides and an outlook on remaining challenges and next research steps in the area of rotor hub flows is provided.

Time scales of dynamic stall development on a vertical-axis wind turbine blade

Vertical-axis wind turbines are excellent candidates to diversify wind energy technology, but their aerodynamic complexity limits industrial deployment. To improve the efficiency and lifespan of vertical-axis wind turbines, we desire data-driven models and control strategies that take into account the timing and duration of subsequent events in the unsteady flow development. Here, we aim to characterise the chain of events that leads to dynamic stall on a vertical-axis wind turbine blade and to quantify the influence of the turbine operation conditions on the duration of the individual flow development stages. We present time-resolved flow and unsteady load measurements of a wind turbine model undergoing dynamic stall for a wide range of tip-speed ratios. Proper orthogonal decomposition is used to identify dominant flow structures and to distinguish six characteristic stall stages: the attached flow, shear-layer growth, vortex formation, upwind stall, downwind stall and flow reattachment stage. The timing and duration of the individual stages are best characterised by the non-dimensional convective time. Dynamic stall stages are also identified based on aerodynamic force measurements. Most of the aerodynamic work is done during the shear-layer growth and the vortex formation stage which underlines the importance of managing dynamic stall on vertical-axis wind turbines.

Performance analysis of a vertical axis wind turbine using computational fluid dynamics

Vertical axis wind turbines (VAWTs) have gained popularity in the last few decades due to their numerous advantages when deployed in urban areas. Despite this, Vertical axis wind turbines have complex aerodynamics, dynamic stall, hence lower performance. Low/zero starting torque, noise, visual impact, as well as blade safeness are further hurdles when they are fitted into the physical environment. Due to these pertinent issues that comes to play in a vertical axis wind turbine, the current investigation explores an augmented vertical axis wind turbine (AVAWT) having a rotor and a stator. The outcome of the study highlighted the effect of mesh density and the type of turbulence model selected in the determination of the forces being exerted on the blade using computational fluid dynamics. Investigation into the effect of time steps showed lesser effect of this parameter on the performance of the blade computationally. The newly developed augmented turbine blades improved the output power by 1.35 times in comparison to an open rotor. The shape for the conical surface and the stator blade impacted the performance as well. Furthermore, it was deduced that there was higher dynamic stall for scenarios where the tip speed ratios were lower. The study showed the importance of the stator in a vertical axis wind turbine in ensuring that the incoming wind attains some acceleration as well as creating a lower pressure outlet but overall aids in the improvement of the power and torque coefficients by more than 36%.

An insight on the key factors influencing the accuracy of the actuator line method for use in vertical-axis turbines: Limitations and open challenges

Darrieus vertical-axis turbines are known for their complex aerodynamics connected to the continuous change in the angle of attack experienced by the blades, which often exceeds the static stall limit. Low fidelity tools such as the Blade Element Momentum Theory have been shown lately not to provide sufficient levels of accuracy, while the medium-fidelity Actuator Line Method (ALM) has been increasingly applied to Darrieus rotors. In this method, the blade-flow interaction is modeled as an equivalent momentum loss calculated introducing equivalent aerodynamic forces into the computed Computational Fluid Dynamics (CFD) domain. This strongly reduces the computational cost in comparison to blade-resolved CFD, allowing ALM to be used in three-dimensional problems, e.g., multiple rotors, floating offshore, etc. While several corrections and guidelines have been recently proposed to tailor ALM to Darrieus turbines, issues are still open on how to improve accuracy.The present study aims at assessing to what extent the three main factors of the ALM theory, namely the quality of input polar, the dynamic stall modeling, and the force insertion in the domain, influence the overall accuracy of the method. In particular, this unprecedented understanding is enabled by the novel use of a “frozen ALM”, i.e., an ALM method fed by the aerodynamic forces calculated by blade-resolved CFD, which allowed to separate the contributions coming from airfoil performance analysis and force projection in the domain. Based on the results, three main important conclusions are drafted out: i) for high and medium tip-speed ratios, provided that the aerodynamic forces are correct, the ALM method is able to generate extremely accurate solutions of the flow field, almost equivalent to blade-resolved CFD; ii) the relevance of the kernel’s shape and smearing function is largely overestimated and current knowledge is adequate for the model to be set; iii) a better dynamic stall model is indeed the real key factor that could lead to an improvement of the ALM accuracy.

Adaptive Control of Flapping-Wing Micro Aerial Vehicle with Coupled Dynamics and Unknown Model Parameters

With the complex aerodynamics, the accurate system model of the flapping-wing micro aerial vehicle required for precise control is hard to acquire, meanwhile, due to the unique control strategy, the coupling between the actuators also brings a great challenge to the control of the vehicle. In this paper, we establish a theoretical model of the vehicle. Based on this model, we propose a multiaxial adaptive controller with the reference generator for the attitude and altitude control using the backstepping design method, the stability of this controller is proved by the Lyapunov function. Moreover, a control allocation algorithm is proposed to coordinate the different actuators such that they together produce the desired virtual control efforts. In addition, we detail the lightweight design of the flapping-wing micro aerial vehicle with altitude and attitude sensing onboard. Then, the effectiveness of the proposed control scheme is verified by the simulation and the flight test with multi-axis simultaneous control conducted on this lightweight vehicle. The experimental results show that the controller can maintain hovering flight and ensure the convergence of the adaptive parameters even when the unilateral thrust of the vehicle is not enough due to manufacturing and assembly errors. This work provides an idea for us to explore how insects maintain stable flight in the face of changes in their model parameters.

Three-dimensional modeling and investigation of the flow around a troposkein vertical axis wind turbine at different operating conditions

Vertical axis wind turbines of troposkein architecture are among the most attractive technologies for harvesting wind energy off-shore. In this paper, a high-fidelity Computational Fluid-Dynamics model of the flow around troposkein rotors is presented, experimentally validated, and applied to analyze the complex aerodynamics of this machine considering both operation and design aspects. At first, a set of two-dimensional simulations of the machine equatorial section was carried out to compare multiple spatial resolutions and three eddy-viscosity turbulence models, including Spalart–Allmaras, k-ω SST, and k-ω SST in low-Reynolds formulation, using as reference wind-tunnel experimental data. Then, the results of fully three-dimensional simulations for peak power and high TSR conditions are discussed, to further assess the models against experiments and to investigate the turbine aerodynamics and its spanwise variability, the flow around and downstream of the rotor, with particular emphasis on the peculiar character of troposkein rotor wake and the related tip vortices. Finally, the paper proposes an analysis about the impact of blade design on the machine aerodynamics, showing that rotors obtained with the simplest and most economic blade bending procedure outperforms configurations obtained by manufacturing the blades with plane airfoil sections along the troposkein curve.

High-fidelity aeroelastic analyses of wind turbines in complex terrain: fluid–structure interaction and aerodynamic modeling

Abstract. This paper shows high-fidelity fluid–structure interaction (FSI) studies applied to the research wind turbine of the WINSENT (Wind Science and Engineering in Complex Terrain) project. In this project, two research wind turbines are going to be erected in the south of Germany in the WindForS complex-terrain test field. The FSI is obtained by coupling the CFD URANS–DES code FLOWer and the multiphysics FEM solver Kratos Multiphysics, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modeling approaches strongly differ with respect to computational resources, and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single-blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low-velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the damage equivalent loading (DEL) is discussed, showing that flexibility reduces the DEL in the case of turbulent inflow, acting as a damper that breaks larger cycles into smaller ones.

Study on Numerical Algorithm of the N-S Equation for Multi-Body Flows around Irregular Disintegrations in Near Space

There has been a concern that the accurate numerical simulation of multi-body flow, which is caused by the multiple disintegrations of expired spacecraft re-entering into the near space, has a critical bottleneck impact on the falling area of the disintegrated debris. To solve this problem, an O-type grid topology method has been designed for the multi-body flow field of irregular debris formed by multiple disintegrations in near space, and a finite-volume implicit numerical scheme has been constructed for the Navier-Stokes equations to solve the aerodynamic interference characteristics of irregular multi-body flow, and further the N-S equation numerical algorithm has been established for the irregular multi-body flows in near space. The reliability of the method has been verified by the comparison of the present computation and the experiment of the low-density wind tunnel for the two-body flow of sphere, cylinder and square scripts. The objects of this study are from the multiple disintegrations of the Tiangong-1 spacecraft during uncontrolled re-entry into the atmosphere, including propelling cylinders and low-temperature lock cabinets. A series of simulations of multi-body flow mechanisms around different combinations have been carried out with varied shapes and spacing. As a result, it is found that when the distance of irregular debris (e.g., two propelling cylinders) in the near space is in the range of Δy < 3D or Δx < D, there is an obvious multi-body interference between debris, and the flow characteristics are obviously changed. When the distance between the debris in near space reaches a certain level, the influence of mutual interference can be ignored. For example, when the y-direction distance between multiple bodies is greater than 3D, the flow interference tends to be small and can be ignored, and we can regard them as two separate pieces to be carried out by the numerical prediction of flight track and falling area in engineering application. The results provide a practical design criterion for the integrated simulation platform which is used to simulate the multi-physics complex aerodynamics of space vehicles from the free-molecule flow of the outer space to the near-ground continuum flow.

A Numerical Aerodynamic Analysis on the Effect of Rear Underbody Diffusers on Road Cars

The aerodynamic complexity of the underbody surfaces of conventional road vehicles is a matter of fact. Currently available literature is focused mainly on very simple Ahmed-body geometries as opposed to realistic car shapes, due to their complexity and computational cost. We attempted to understand the flow behaviour around different realistic conventional road car geometries, and we provide an extensive evaluation of the aerodynamic loads generated. The key findings of this article could potentially set a precedent and be useful within the automotive industry’s investigations on drag-reduction mechanisms or sources of downforce generation. The novelty of the work resides in the realistic approach employed for the geometries and in the investigation of barely researched aerodynamic elements, such as front diffusers, which might pave the way for further research studies. A baseline flat-underfloor design, a 7∘ venturi diffuser-equipped setup, a venturi diffuser with diagonal skirts, and the same venturi diffuser with frontal slot-diffusers are the main configurations we studied. The numerical predictions evaluated using RANS computational fluid dynamics (CFD) simulations deal with the aerodynamic coefficients. The configuration that produced the highest downforce coefficient was the one composed of the 7∘ venturi diffuser equipped with diagonal sealing skirts, achieving a CL value of −0.887, which represents an increase of around 1780% with regard to the baseline model. That achievement and the gains in higher vertical loads also entail a compromise with an increase in the overall air resistance. The performance achieved with diffusers in the generation of downforce is, as opposed to the one obtained with conventional wings, a cleaner alternative, by avoiding wake disturbances and downwash phenomena.

Adaptive fault-tolerant control of a novel ducted-fan aerial robot against partial actuator failure

This research is aimed at an adaptive fault-tolerant control scheme for a special ducted-fan aerial robot against partial actuator failure. Although the ducted-fans are widely used in aircraft propulsion systems, their aerodynamic complexity is an enormous challenge for fault-tolerant control. This paper proposes an adaptive control mechanism based on an identified state-space model in the frequency domain. The fault-tolerant controller includes a robust baseline loop and an adaptive loop. The adaptive loop is coupled with an estimator and a reconfigurable adjust law to estimate the actuator failure and compensate for different degrees of failure. The performance of the algorithm is verified by theoretical simulations and real-time flight experiments.