Unmanned Aerial Vehicle Helicopter Research Articles

Investigating and Analyzing the Potential for Regenerating Excess Energy in a Helicopter UAV

Energy consumption is a critical parameter in the development of helicopter Unmanned Aerial Vehicles (UAVs). Today, helicopter UAVs are playing an increasingly pivotal role in various applications, from surveillance and reconnaissance to package delivery and search and rescue missions. However, their energy efficiency remains a pressing issue, as it directly impacts their operational duration and payload capacity. One of the key challenges in optimizing energy consumption is the existence of excess power during flight, arising from the intricate interplay between helicopter aerodynamic behavior and safety design. Typically, this excess energy is dissipated, resulting in a suboptimal performance and efficiency. This study investigated the behavior of excess power in a helicopter Unmanned Aerial Vehicle (UAV). Typically, this excess energy is wasted in conventional helicopters and helicopter UAVs. A dual-method approach, encompassing numerical and experimental methodologies, was employed to provide comprehensive insights into the helicopter UAV’s performance under various conditions. Computational fluid dynamics (CFD) simulations were performed to analyze the UAV’s aerodynamics. The simulations were validated by comparing the lift force with wind tunnel experimental data, resulting in acceptable deviations. The experimental analysis was conducted using a wind tunnel and a small-sized helicopter UAV. The experiments were designed to examine the excess power behavior of the UAV under two distinct flight conditions: hover and forward flight. The power output from the generator and power input from the battery were measured under various angular velocities and pitch angles. The results revealed a maximum excess power of 6.84% for hover conditions and 9.83% for forward flight conditions. This indicates that the maximum excess power percentage attributable to the helicopter UAV’s safety measure is 6.84% and that resulting from aerodynamics is 2.99%. The findings of this study contribute valuable knowledge to the optimization of helicopter UAV performance and the potential for harnessing excess power during flight operations. When this excess energy is harnessed, it can contribute significantly to the overall performance and efficiency of the UAV, potentially extending its flight duration or accommodating additional payload capacity that could potentially pave the way for the development of hybrid helicopter UAV models in the future.

Characteristic calculations of antennas for communication and retransmission placed on aircraft and helicopter unmanned aerial vehicles

The issues of increasing the communication range when organizing data transfer between two remote sites are especially important and very relevant. An increase in the communication range can be achieved by increasing the height of the antennas. One of the effective technical solutions that allow placing antennas and radio stations at high altitude in the required place is the use of modern unmanned aerial vehicles (UAV). Target. Calculations and studies of the characteristics of antennas placed on UAV of various types. The results of calculations of the energy and spatial characteristics of three types of antennas installed on UAV of various types are obtained: asymmetric whip antenna; a low-profile antenna consisting of three PIFA emitters; an annular antenna array consisting of 6 asymmetric Uda-Yagi antennas. It is shown that each of the solutions has its own advantages and disadvantages and its own scope. Based on the obtained results of calculating the characteristics of antennas, the developers of the corresponding communication systems can make a reasonable choice of the types of antennas used, depending on the requirements for the systems as a whole.

UAV-based magnetometry — Practical considerations, performance measures, and application to magnetic anomaly detection

Interest in ubiquitous low-cost unmanned aerial vehicles (UAVs) for use in aeromagnetic surveying has grown dramatically over the past decade. While their appeal is alluring, caution is called for as high-quality airborne magnetometry requires diligent system design and performance qualification. This paper discusses considerations and trade-offs in UAV-based magnetometry, standard measures to qualify performance, and application to magnetic anomaly detection (MAD). The apparent simplicity of towed-bird installations needs careful consideration. Logistical complexities, stability, and safety issues aside, critical compensation for time-varying swing effects is seldom, if at all, standard practice. While well-compensated fixed-mount sensor installations are preferable, they require careful attention to a number of unique aspects including the complex magnetic signatures of typical UAVs. The paper introduces a novel anomaly detection method that is based on the entropy of the total-field magnetometer signal, gated by an analogous measure obtained from a vector magnetometer. Two field studies using a fixed-mount single-magnetometer configuration on a helicopter UAV empirically demonstrate the application of the performance measures and the performance of the MAD method. Notably, the latter clearly illustrates the importance of sound aeromagnetic compensation and enhances the output of an earlier entropy-based detection method.

Helicopter–UAVs search and rescue task allocation considering UAVs operating environment and performance

The task allocation of unmanned aerial vehicles (UAVs) is important in UAV search and rescue to guarantee an effective and orderly search and rescue activity. However, few studies have investigated the influences of the UAV operating environment and performance on search and rescue task allocation. Considering the influences of low-altitude wind and terrain on UAV energy consumption and performance, UAV release position (from helicopter) selection and task allocation models are proposed in this study. Given that the detection zone of UAVs is affected by topographic factors, the principal component analysis method was used to determine the search and rescue level at each search and rescue point and the UAV hovering endurance, which was determined using clustering analysis. Considering the influence factors of UAV battery energy consumption, such as UAV performance and low-altitude wind, an UAV release position selection model was constructed and solved via the improved binary bat algorithm which exhibited enhanced calculation accuracy comparing with three other algorithms. According to the release position planning result, a multi-objective (minimization of the total search and rescue cost and number of UAVs and multi-UAV task balance) optimization model was established and solved using the non-dominated sorting genetic algorithm-II. Finally, the experimental results indicated that the solution through multiple objectives had no cost advantage comparing with those under the single objective, but exhibited an evident advantage in task completion time through sensitivity analysis of UAVs task allocation problem.

Flight Dynamics and Control of an Unmanned Helicopter with Underslung Double Pendulum

This paper presents systematic modeling and simulation of the dynamics and control of a carrier helicopter unmanned aerial vehicle (UAV) with a suspended net used for capturing target UAVs. The goal is to study the effect of key design parameters such as the weight of the net end rod, its length, and point of impact of the UAV on the swing angle of the underslung net. First, a net with an entangled target UAV is modeled as a planar double pendulum. Next, the coupled flight dynamic model of carrier UAV with underslung net with entangled target UAV is simulated and validated using the test data gathered for this purpose. From the simulations, it is identified that the length of the net and point of capture of the UAV on the net are critical parameters that govern the maximum swing angles of the double-pendulum system. Moving the point of impact of the target UAV by 10% of net length resulted in up to 23 and 43% reduction in swing angles of pendulums 1 and 2. The active swing suppression using proportional derivative (PD) controller is effective in attenuating the swing angles in the simulation for successful capture.

Chaos control of small-scale UAV helicopter based on high order differential feedback controller

ABSTRACT The small-scale unmanned aerial vehicle (UAV) helicopter has a complex structure, strong nonlinearity, coupling and open-loop instability, making it shake violently and even produce chaotic oscillation under wind disturbances and improper configuration. The chaotic angular velocity dynamic model of the UAV helicopter is analysed via two cases. The sliding mode controller (SMC) relying on the linearised model, the PID controller, and the high order differential feedback controller (HODFC) not relying on the model are designed. The closed-loop system stability under both SMC and HODFC are analysed. The HODFC with a control filtering can actively reject the disturbance and uncertainty. The control performance of HODFC is superior to SMC and PID controllers. The SMC and HODFC can stabilise the chaotic oscillations of UAV helicopter’s angular velocity, whereas the PID controller fails, and the HODFC control effect is superior to the SMC for disturbance rejection, uncertainty and linearisation bias in steady-state errors.

Actuator Fault Detection and Isolation for Helicopter Unmanned Arial Vehicle in the Present of Disturbance

Helicopter unmanned aerial vehicle (HUAV) are an ideal platform for academic researchs. Abilities of this vehicle to take off and landing vertically while performing hover flight and various flight maneuvers have made them proper vehicles for a wide range of applications. This paper suggests a model-based fault detection and isolation for HUAV in hover mode. Moreover in HUAV, roll, pitch and yaw actuator faults are coupled and affect each other, hence, we need a method that decouples them and also separates fault from disturbance. For this purpose, a robust unknown input observer (UIO) is designed to detect bias fault and also catastrophic fault such as stuck in actuators of HUAV. The robust UIO isolates roll and pitch actuator faults from yaw actuator fault. The novelty of this manuscript is the design of two UIO observers to detect and decouple the faults of helicopter actuators, one for lateral and longitudinal actuators and the other for pedal actuator. Also, the proposed method is compared with extended Kalman filter (EKF). Simulation results show effectiveness of the proposed method for detection and isolation of actuator faults with less number of observers and it is able to decouple fault and disturbance effects.

Robust Three Stage Central Difference Kalman Filter for Helicopter Unmanned Aerial Vehicle Actuators Fault Estimation

This paper proposes state and fault estimations for uncertain time-varying nonlinear stochastic systems with unknown inputs. we suppose, the information about the fault and unknown inputs is not perfectly known. For this purpose, in this manuscript, we developed a robust three-stage central difference Kalman filter (RThSCDKF). We used RThSCDKF for model-based fault detection and identification (FDI) in nonlinear hover mode of helicopter unmanned aerial vehicle (HUAV) in the presence of external disturbance. In this system, actuator faults are affected by each other. The proposed method estimates and decouples actuator faults in the presence of external disturbances. This model can detect stuck and floating faults that are important to detect. At the end, this method is compared with the three-stage extended Kalman filter (ThSEKF). Simulation results show the effectiveness of the proposed robust method for detection and isolation of various actuator faults and also this shows more accuracy with respect to ThSEKF.

Actuator Faults Estimation for a Helicopter UAV in the Presence of Disturbances

The aim of this paper is to develop robust three-stage extended Kalman filter for a model based on a fault detection and identification for nonlinear hover mode system of helicopter unmanned aerial vehicle. In addition, we show that, in considered systems, the actuator faults are affected by each other motivated in five scenarios simulation results. More precisely, the proposed approach estimates and decouples actuator faults in the presence of external disturbances in nonlinear mathematical model. Moreover, we analyze and identify various faults such as bias fault and also catastrophic faults such as stuck and floating faults. Finally, the simulation results show effectiveness of the proposed robust method for detection and isolation of various actuator faults and differentiating bias and stuck faults.

Research on unmanned aerial vehicle modeling and control based on intelligent algorithms

This article designs an automatic flight control system for an unmanned aerial vehicle helicopter. The differential evolution intelligent algorithm is used for a state-space model identification; the differential evolution method has an advantage of choosing initial point randomly. The accuracy of the identified model is verified by comparing the model-predicted responses with the responses collected during flight experiments. The reliability and efficiency of the differential evolution algorithm are demonstrated by the experimental results. A robust controller is designed based on the identified model for the unmanned aerial vehicle helicopter with two-loop control frame: the outer-loop is used to obtain the expected attitude angles through reference path and speed with guidance-based path-following control, and the inner-loop is used to control the attitude angles of helicopter tracking the expected ones with H∞ loop-shaping method. The greatest common right divisor method is used to choose the weighting matrix in loop shaping, in which the stability margin is larger and has a greater bandwidth of the unmanned aerial vehicle system. Finally, a space spiral curve trajectory tracking simulation is conducted to illustrate the efficiency of the proposed control systems, and the simulation results prove that the unmanned helicopter system achieves a top-level control performance.

Numerical Investigations of Aerodynamics Characteristics of Main Rotors in Helicopter UAV Used for Pesticide Spraying in Agriculture

In the last several decades past, Helicopters UAVs (Unmanned Aerial Vehicles) have quickly developed and day by day, they play an important role in human life. As it is well-known, helicopters UAV make some outstanding characteristics such as light weight, flexibility and particularly automatically controlled. By applying these characteristics, we research and manufacture Helicopter UAV using for spraying pesticide in agriculture. One of the most important components is main rotor because main rotor generated thrust, drag and momentum. Helicopters UAV efficient changed depending on main rotor. The research works focus on aerodynamics characterization of main rotor in helicopter UAV. This work uses CFD tool in ANSYS CFX software to calculate the aerodynamics parameters generated by main rotor using in UAV. The aim is to characterize the aerodynamics characteristics such as thrust, drag, pressure, aerodynamics quality on the different flight modes (hover, vertical and forward flight). Firstly, the simulations are carried out in hover flight mode with different blade pitch angles. The results are compared to experiment date in another research to validate numerical results. Then, the simulations are carried out in vertical flight mode and forward flight mode. The results showed that thrust and drag coefficient creased with increasing blade pitch angle. When blade pitch angle started from 1800, thrust coefficient decreased but drag coefficient increased sharply. The rotor performance was measured by aerodynamics quality and numerical results showed that the best rotor performance was at 900. In the vertical flight mode, the thrust and drag coefficient decreased with increasing vertical velocity but rotor performance increased slightly. The best vertical velocity for vertical flight is around 2 m/s and 3 m/s. Finally, in forward flight mode, the aerodynamics characterizations of rotors depended on azimuthal angular position of blade or time. Our helicopter operates in environment with light gust. The results showed the change of aerodynamics coefficient to time. Both thrust and drag coefficient changed but the rotor performance did not change much.

Adaptive finite-time reconfiguration control of unmanned aerial vehicles with a moving leader

This paper investigates adaptive reconfiguration control problem for unmanned aerial vehicle (UAV) helicopter system with a moving leader. Only part of UAV helicopter is informed to have access to the leader’s position. The six degree-of-freedom UAV system is composed of position outer loop and attitude inner loop. In this paper, we introduce a new fully distributed, finite-time reconfiguration controller and the problem of inter-UAVs collision avoidance was solved using potential energy function approach, extending the asymptotical formation controller without collision avoidance from the literature. The distinctive feature of our algorithm from existing works is that the novel formation reconfiguration controller can achieve finite-time, collision avoidance and fully distributed formation only based on relative positions between UAV and its adjacents. It means that the control algorithm is independent of any global information that requires to be calculated by each follower UAV. The system uncertainties are estimated by radial basis function neural network in practical finite time. Simulation results are shown to demonstrate the efficiency of the designed strategy.

Finite‐time fully distributed formation reconfiguration control for UAV helicopters

SummaryThis paper studies finite‐time fully distributed formation and reconfiguration control of multiple unmanned aerial vehicle helicopter with disturbances and uncertainty. Based on adaptive and terminal sliding‐mode control techniques, a disturbance observer‐based fully distributed control strategy is proposed, which is independent of least nonzero eigenvalue of Laplacian matrix and achieves practical finite‐time formation tracking for a moving leader without any additional condition. The proposed method is proved superior to the existing method in converging time. The finite‐time stability of the closed‐loop error is proved by the Lyapunov theory. Considering formation configuration changing as a result of a task change, a modified finite‐time fully distributed controller including potential energy function gradient terms with an adaptive law is proposed. The novelty of the reconfiguration controller is that an adaptive law is firstly integrated in the gradient items, then the asymptotical stability is extended to practical finite‐time stability. Simulation results are presented to demonstrate the efficiency of the developed algorithm.

A new information-weighted recursive algorithm for time-varying systems: application to UAV system identification

ABSTRACTThis paper presents a new recursive identification method which can efficiently estimate time-varying parameters in discrete time systems and has significant advantages over standard recursive least-squares (RLS) method. This new information-weighted recursive algorithm for time-varying systems has three novel features, discounting of inaccurate estimates through weighting by the Information matrix, using the reuse of past data in computing current parameter estimates, a new tuneable damping factor parameter and a precisely designed compensation term to neutralise the estimation error caused by time-varying coefficients. A rigorous proof of convergence is also provided. Simulations show that the new algorithm significantly outperforms standard RLS, exhibiting better tracking performance and faster convergence. Flight tests on a T-REX 800 helicopter Unmanned Aerial Vehicle platform show that it gives system parameter estimates that are accurate enough and converge quickly enough that flight controllers can be designed in real-time based on the online identified model.

UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS AND HYPERSPECTRAL IMAGING FOR MAPPING BIODIVERSITY INDICATORS IN BOREAL FORESTS

Abstract. Biodiversity is commonly referred to as species diversity but in forest ecosystems variability in structural and functional characteristics can also be treated as measures of biodiversity. Small unmanned aerial vehicles (UAVs) provide a means for characterizing forest ecosystem with high spatial resolution, permitting measuring physical characteristics of a forest ecosystem from a viewpoint of biodiversity. The objective of this study is to examine the applicability of photogrammetric point clouds and hyperspectral imaging acquired with a small UAV helicopter in mapping biodiversity indicators, such as structural complexity as well as the amount of deciduous and dead trees at plot level in southern boreal forests. Standard deviation of tree heights within a sample plot, used as a proxy for structural complexity, was the most accurately derived biodiversity indicator resulting in a mean error of 0.5 m, with a standard deviation of 0.9 m. The volume predictions for deciduous and dead trees were underestimated by 32.4 m3/ha and 1.7 m3/ha, respectively, with standard deviation of 50.2 m3/ha for deciduous and 3.2 m3/ha for dead trees. The spectral features describing brightness (i.e. higher reflectance values) were prevailing in feature selection but several wavelengths were represented. Thus, it can be concluded that structural complexity can be predicted reliably but at the same time can be expected to be underestimated with photogrammetric point clouds obtained with a small UAV. Additionally, plot-level volume of dead trees can be predicted with small mean error whereas identifying deciduous species was more challenging at plot level.

Analysis of preliminary design requirements of a heavy lift multirotor drone for agricultural use

Within the civil aviation cluster, the technological applications in agriculture represent a booming field consisting in acquisition of data through remote sensing and integration of sensor networks (crop status detection) or development of chemical and biological treatment applications. Drones in agriculture can be used for a variety of task, aimed to increase farm crop yields and accurately monitor fields, simultaneously decreasing time, labour and resources. While for some specific task a medium size drone can be chosen, on the other hand for other task like precision spraying of pesticide or fertilizer heavy lift drone are required. Prior to the approval of Yamaha R-MAX, an UAV helicopter which will be allowed to operate with a maximum payload of 98 kg, the Federal Aviation Administration (FAA) had only issued exemptions for much smaller drones weighing less than 55 pounds (24.98 kg). In Europe national legislations still lack of harmonization, and in Italy at the moment the local legislation restricts the possible choices to a maximum allowed take-off weight of 25kg without the necessity to submit a “permit to fly” documentation which is equivalent to the one required for a full scale commercial vehicle. Depending on the required task, one of the more important tasks of designing a multirotor Unmanned Aerial Vehicle (UAV) is the selection of a propulsion system that will provide desired performance in terms of payload and flight length or duration. Rigorous methods for selecting these drive components, that is, the motors, propellers, and batteries for electric UAVs are not readily available. A possible choice relies on using a Ready To Fly (RTF) UAV, but rapid changes in components and a fast evolution of the performance of engines and batteries allow possible updates of the existing UAV using aftermarket part to increase the flight envelope, a particularly interesting feature for heavy lift drone if a proper design method is adopted. Moreover, integration of technologies like LIDAR is easier to implement on UAV in which the design is not proprietary. In this work the technical requirements for agricultural tasks are investigated, and the state of the art of drone design method is presented, reporting an analysis of actual possibilities in terms of payload/flight envelope.

Yaw control of an unmanned aerial vehicle helicopter using linear active disturbance rejection control

In this article, a yaw channel controller with linear active disturbance rejection control is proposed for high-performance attitude tracking of an unmanned helicopter. In this control scheme, the linear extended state observer serves as a compensator, which can effectively reject parametric uncertainties and external disturbances. In this case, the attitude tracking controller is designed according to the input–output relation of yaw model. As a controlled plant, the yaw dynamical model is first obtained through the system identification method. Subsequently, in order to optimize the linear active disturbance rejection control applied to yaw control, an artificial bee colony algorithm is introduced to solve the problem of parameter tuning. Finally, comparative studies are carried out. The results from simulation and flight experiment show that the proposed controller provides better performances than the traditional controller.

Design and implementation of atmospheric multi-parameter sensor for UAV-based aerosol distribution detection

PurposeIn this paper, a light-weight, low-power atmospheric multi-parameter sensor (AMPS), which could be mounted on small flying platforms such as a tethered balloon, a quad-rotor unmanned aerial vehicle (UAV), a UAV helicopter, etc., is implemented and integrated to sample vertical distribution of aerosols with integrated parameters of aerosol particle concentration, temperature, relative humidity and atmospheric pressure.Design/methodology/approachThe AMPS integrates three kinds of probes in an embedded system. A synchronous method based on GPS is proposed to drive the laser aerosol particle sensor, the temperature and humidity probe and the pressure probe to sample four channels approximately simultaneously. Different kinds of housing are designed to accommodate various flying platforms, and the weight is controlled to adapt the payload of each platform.FindingsA series of validation tests show that while the AMPS achieves high precision, its power consumption is less than 1.3 W, which is essential for light flying platforms. The AMPS was mounted on different flying platforms and the difference was evaluated. For three times every five days, vertical profiles of PM2.5 and PM10 concentrations were observed by the AMPS mounted on a quad-rotor UAV, which revealed the significant correlation between the aerosol particle concentration and atmospheric parameters.Originality/valueA new light-weight and low-power AMPS for small flying platforms is designed and tested, which provides an effective way to explore the properties of aerosol vertical distribution, and to monitor pollutants flexibly.

Adaptive fuzzy tracking control for non-affine nonlinear yaw channel of unmanned aerial vehicle helicopter

The article deals with the problem of the yaw control of the unmanned aerial vehicle helicopter which is non-affine nonlinear by use of a novel projection-based adaptive fuzzy control approach. First, principle model and control design model of the yaw channel of the unmanned aerial vehicle helicopter are described. Then, a dynamic approximation technique is introduced to approach the non-affine model of the unmanned aerial vehicle helicopter into an affine model with variable parameters, which is applied to facilitate the design of nonlinear control scheme. Next, in the proposed controller, fuzzy controller is designed to deal with the unknown uncertainties and disturbances. Meanwhile, the projection-based adaptive law applied in fuzzy controller bounds the parameter estimation function and can also guarantee the robustness of the designed control scheme against uncertain disturbances. Moreover, the convergence and stability of the designed controller are proved by Lyapunov stability theory. Finally, the simulation results of the yaw channel of an unmanned aerial vehicle helicopter are performed to illustrate that the designed controller has good tracking performance, stability, and robustness under the condition of the time-vary uncertain disturbances.

Clustered Event-Triggered Consensus Analysis: An Impulsive Framework

This paper proposes an impulsive framework to analyze the effect of the clustered event-triggered information transmission on the dynamics of multiagent systems. Under this framework, we study three cases and propose different types of event-triggered protocols. First, if agents’ states are available, a clustered event-triggered protocol based on agents’ states is designed, which guarantees all followers to track the leader eventually. Second, the first case is further investigated when the agents’ states are under disturbance. Hence, a modified event-triggered protocol is introduced to reach $\mathcal {L}_\infty$ leader-following consensus. Third, for the case where agents’ states are not available, a clustered event-triggered observer-type protocol is developed based on the agents’ outputs. It is worth noting that Zeno behavior is excluded in these cases. Finally, some numerical examples and an application of unmanned aerial vehicle helicopters are given to verify our theoretical analysis.