External Wind Disturbances Research Articles

Active Disturbance Rejection Flight Control and Simulation of Unmanned Quad Tilt Rotor eVTOL Based on Adaptive Neural Network

The unmanned quad tilt-rotor eVTOL (QTRV) is a variable-configuration aircraft that combines the features of vertical takeoff and landing (VTOL), hovering, and high-speed cruising, making its control system design particularly challenging. The flight dynamics of the QTRV differ significantly between the VTOL and cruise modes, and are further influenced by rotor tilt and external wind disturbances. Developing a unified, highly coupled nonlinear full-flight dynamics model facilitates flight control system design and simulation verification. To ensure stable tilt of the QTRV, a tilt corridor was established, along with the design of its tilt route and manipulation strategy. An adaptive neural network active disturbance rejection controller (ANN-ADRC) is proposed to ensure stable flight across all modes, reducing the control parameters and simplifying tuning while effectively estimating and compensating for unknown disturbances in real time. A hardware-in-the-loop (HIL) simulation system was designed for full-mode flight control simulation, and the results demonstrated the effectiveness of the proposed control method.

Hierarchical gain scheduling based tilt angle guided robust control during mode transition for tilt-rotor unmanned aircraft vehicle

Tilt-rotor unmanned aircraft vehicle has the potential to combine vertical take-off and landing capability with efficient, high-speed cruise flight. However, the mode transition process is risky owing to the internal continuous time change of aerodynamic and external uncertain wind disturbances. Gain scheduling between two modes is commonly used to achieve mode transition control. However, the optimal scheduling parameters to allocate the manipulated variables for the stable transition have not been determined to data. Focusing on this problem, a gain scheduling-based tilt angle guided robust control method for mode transition is proposed. The dynamic model is first built and analyzed based on a newly developed 360-kg tilt-rotor unmanned aircraft vehicle. Based on this model, the transition guided curve is mapped with respect to velocity and tilt angle, and it is introduced to the gain scheduling method to optimally achieve the allocation of the manipulated variables. Finally, the feasibility and validity are verified in a simulation experiment. Furthermore, the robustness is verified in simulated wind disturbance.

UAV trajectory tracking under wind disturbance based on novel antidisturbance sliding mode control

With the widespread application of unmanned aerial vehicles, harsh environments require higher control performance. Numerous existing works offer solutions for handling external disturbances during flight; however, the timeliness of the disturbance compensation is rarely discussed. This study focuses on trajectory tracking under external wind disturbances, specifically under two types of interference: average wind and wind shear. After compensating for the disturbance, a novel antidisturbance sliding mode control is designed based on reference model, to realize accurate, robust, and chatterless trajectory tracking under wind disturbance. Firstly, we addressed the limitations of conventional extended state observers, nonderived forms, and inadequate use of information by introducing state compensation function observers to enhance estimation accuracy for states and disturbances that are challenging to measure directly. Moreover, the disturbance variation is estimated using tracking differentiator and then compensated in the controller to enhance antidisturbance sensitivity. In addition, the effectiveness and stability of the proposed observer and controller are analyzed. Finally, a two-step verification is presented, including simulation with input disturbances and actual flight under two wind field types; multiple industrial fans are used to generate the average wind and wind shear during the experiment. Two robust control methods, state-of-the-art active disturbance rejection control and sliding mode control, are also implemented for comparison, and the results indicate that more than 61.2% accuracy improvement over comparison methods is achieved in simulation and actual experiments.

Precision Landing of Unmanned Aerial Vehicle under Wind Disturbance Using Derivative Sliding Mode Nonlinear Disturbance Observer-Based Control Method

Unmanned aerial vehicles (UAVs) are extensively employed in civilian and military applications because of their excellent maneuverability. Achieving fully autonomous quadrotor flight and precision landing on a wireless charging station in the presence of wind disturbance has become a crucial research topic. This paper presents a composite control technique for UAV altitude and attitude tracking in harsh environments, i.e., wind disturbance. A composite controller was developed based on nonlinear disturbance observer (NDOB) control theory to allow the UAV to land in the presence of random external wind disturbances and ground effects. The NDOB estimated the unknown wind disturbance, and the estimation was fed into the derivative sliding mode nonlinear disturbance observer-based control (DSMNDOBC), allowing the UAV to perform autonomous precision landing. Two loop designs were applied: the inner loop for stabilization and the outer loop for altitude tracking. The quadrotor model dynamics and the proposed controller, DSMNDOBC, were simulated employing MATLAB/Simulink®, and the results were compared with the one obtained by the proportional derivative (PD) controller and the sliding mode controller (SMC). The simulation results indicated that the DSMNDOBC has superior altitude and attitude control compared to the PD and SMC controllers and better disturbance estimation and attenuation performance.

Dynamic Modeling and Altitude Control for Flying Cars Based on Active Disturbance Rejection Control

Flying cars offer huge advantages due to their deformable structure, which can adapt to external environments and mission requirements. They represent a novel system that can realize vertical takeoff and landing. However, the structure of a flying car is complicated, placing higher requirements on modeling accuracy and control effectiveness. Thus, in this paper, a dynamic model of a flying car is proposed by combining a car body, motor, and propellers. Then, a double-loop controller based on active disturbance rejection control is proposed to accurately control its flight altitude. Utilizing the extended state observer, external wind and other disturbances are regarded as an extended state, which can be dynamically observed and compensated to significantly improve tracking accuracy. The effectiveness of the proposed controller is validated through detailed simulations and flight experiments. The proposed controller significantly improves control accuracy and disturbance rejection capability.

Design and Real-Time Implementation of a Cascaded Model Predictive Control Architecture for Unmanned Aerial Vehicles

Modeling and control are challenging in unmanned aerial vehicles, especially in quadrotors where there exists high coupling between the position and the orientation dynamics. In simulations, conventional control strategies such as the use of a proportional–integral–derivative (PID) controller under different configurations are typically employed due to their simplicity and ease of design. However, linear assumptions have to be made, which turns into poor performance for practical applications on unmanned aerial vehicles (UAVs). This paper designs and implements a hierarchical cascaded model predictive control (MPC) for three-dimensional trajectory tracking using a quadrotor platform. The overall system consists of two stages: the mission server and the commander stabilizer. Different from existing works, the heavy computational burden is managed by decomposing the overall MPC strategy into two different schemes. The first scheme controls the translational displacements while the second scheme regulates the rotational movements of the quadrotor. For validation, the performance of the proposed controller is compared against that of a proportional–integral–velocity (PIV) controller taken from the literature. Here, real-world experiments for tracking helicoidal and lemniscate trajectories are implemented, while for regulation, an extreme wind disturbance is applied. The experimental results show that the proposed controller outperforms the PIV controller, presenting less signal effort fluctuations, especially in terms of rejecting external wind disturbances.

A Bio-Inspired Safety Control System for UAVs in Confined Environment With Disturbance.

This article presents a bio-inspired safety control scheme for unmanned aerial vehicles (UAVs) in confined environments with disturbance. Although there has been some existing research on the effect of disturbance for a single UAV, multi-UAV formation under external wind disturbances remains challenging, especially in a tight and confined environment. Inspired by nature, this study concentrates on an anti-disturbance mechanism for safe multi-UAV formation in a tight environment. The presented safety control system combines disturbance observer-based control (DOBC), bionic formation switching (BFS) strategy, and safety evaluation. Two safety issues are considered in this article. For a single UAV, the estimated disturbance is compensated in the inner-loop controller. While for multi-UAV formation, the BFS strategy attenuates the effect of external wind disturbance leveraging the formation configuration. The so-called group perturbation immune factor (GPIF) is designed to analyze and evaluate the safety of the overall formation. The experimental results validate the comprehensiveness and anti-disturbance capability of the system.

Design and Control of a Reconfigurable Robot with Rolling and Flying Locomotion

Given the continual rise in mission diversity and environmental complexity, the adept integration of a robot’s aerial and terrestrial locomotion modes to address diverse application scenarios has evolved into a formidable challenge. In this paper, we design a reconfigurable airframe robot endowed with the dual functionalities of rolling and flying. This innovative design not only ensures a lightweight structure but also incorporates morphing capabilities facilitated by a slider-crank mechanism. Subsequently, a land-to-air transformation strategy for the robot is introduced, achieved through the coordinated movement of the robotic arm and the servo motor. To ensure stable control of the robot amid external wind disturbances, we leverage the collaboration between a Generative Adversarial Network (GAN)and a Nonlinear Model Predictive Control (NMPC) controller. After the wind force magnitude is predicted through the neural network, the robot’s adeptness in flexible trajectory tracking is verified. Under simulated wind conditions of 12.1 m/s, the trajectory error consistently remains within the range of 10–15 cm, affirming the effectiveness of this control method.

Adaptive PID Control for Autopilot Design of Small Fixed Wing UAVs

The development of a flight control system for the class of small fixed wing Unmanned Aerial Vehicle (UAV) imposes a challenge to the designers to achieve acceptable and stable performance characteristics across the defined flight envelope. This paper focuses on developing a dynamic model of the Aerosonde UAV, incorporating it with an adaptive Proportional, Integral and Derivative (PID) control system for designing both lateral and longitudinal autopilots. The PID gains for each control loop are self-tuned based on an analytical approach, making sure that the desired command value is achieved at each time interval as closely as possible. To check the robust nature of the designed control system in the presence of external wind disturbance, a Dryden wind gust model was developed, and the entire simulation results were carried out in MATLAB®/Simulink environment. The proposed adaptive PID controller proves the effectiveness and robustness of the autopilot control system.

Fixed‐time disturbance observer‐based fixed‐time path following control for small fixed‐wing UAVs under wind disturbances

SummaryIn this paper, the three‐dimensional path following control problem for small‐scale fixed‐wing unmanned aerial vehicles (UAVs) subject to external wind disturbances is investigated. A fixed‐time disturbance observer is designed to estimate the external wind disturbance. The estimates are then incorporated into the fixed‐time integral terminal sliding mode controller such that a composite control scheme is proposed. Under the proposed control scheme, the UAV system not only guarantees a fixed‐time convergence rate but also possesses stronger disturbance rejection ability and better robustness. Finally, the effectiveness of this strategy is verified by numerical simulations.

Finite-time control based on RBF neural network for quadrotor UAVs with varied mass load

Aiming at the problem of the gradual reduction of the weight and the external wind disturbance affect flight performance of the quadrotor Unmanned Aerial Vehicle (UAV), a dual-loop finite time control strategy based on Radial Basis Function (RBF) neural network is proposed. The UAV model under disturbance is decoupled into position outer loop subsystem and attitude inner loop subsystem. In the outer loop, the changing weight and the external wind disturbance are approximated by using RBF neural network, command filter is used to avoid the “computing explosion” problem in the traditional backstepping method, and the finite-time control method is able to improve the convergence speed of the position. In the inner loop, the cascade RBF neural network PID control which relies on the self-learning of neural network to realize the dynamic tuning of PID parameters is adopted to achieve rapid convergence of the attitude angle. The simulation results show that compared with the traditional backstepping method and cascade PID control, the convergence time is reduced by 31% on average, which verifies the superiority and effectiveness of the proposed control strategy.

Adaptive path following control for miniature unmanned aerial vehicle confined to three-dimensional Dubins path: From take-off to landing

This study proposes a method for resolving the challenge of controlling miniature fixed-wing unmanned aerial vehicles (MAVs) along a predetermined three-dimensional (3D) Dubins path while using models with uncertainty and when experiencing external wind disturbances. We provide a multilayered structure that incorporates both guiding and control at the same time. In the guidance layer, a modified vector-field-based approach is presented to enable the MAV to follow a 3D Dubins path, including the takeoff, cruise, and landing processes with three different types of route segments. Then, an adaptive sliding model controller is used for the analysis and management of both wind disturbances and system uncertainties. Finally, both simulated scenarios and in-flight trials demonstrate the applicability of the methodology and the efficiency of the proposed approach.

Attitude Control for Quadrotors Under Unknown Disturbances Using Triple-Step Method and Nonlinear Integral Sliding Mode

A cascade controller architecture is designed to realize the attitude control of quadrotor with unknown disturbances in this paper. The cascade controller integrates the advantages of triple-step method and nonlinear integral sliding mode. In the inner loop, an extended high-gain observer is designed to estimate total disturbance including model uncertainty and external wind disturbance in real time. Moreover, a nonlinear integral sliding mode with the capability of small error amplification and large error saturation is introduced to compensate for the estimated disturbance and track desired angular velocity. In the outer loop, a TD-based triple-step controller is designed to guarantee fast tracking of attitude angle. The convergence of tracking errors of both inner and outer loops is proved through Lyapunov theory. Finally, both simulation and experimental results demonstrate the effectiveness of the proposed control method.

Path-Following Control of Small Fixed-Wing UAVs under Wind Disturbance

Aiming at the problems of low following accuracy and weak anti-disturbance ability in the three-dimensional path-following control of small fixed-wing Unmanned Aerial Vehicles (UAV), a Globally Stable Integral Sliding Mode Radial Basis Function S-Plane (GSISM+RBF S-Plane) controller is designed. The controller adopts the inner and outer loop mode, the outer loop adopts the Globally Stable Integral Sliding Mode (GSISM) control, and the inner loop adopts the S-Plane control. At the same time, the unknown disturbance in the model is estimated via an RBF neural network. Firstly, the outer loop controller is designed based on the GSISM, and its stability is proved using the Lyapunov theory. Then, the S-Plane controller is designed for the instruction signal of the inner loop. Considering the complexity of the derivation in the S-Plane controller, a second-order differentiator is introduced. Finally, considering the problem of external wind disturbance, the controller is modeled, studied, and processed in order to better reflect the impact of real external wind on UAV path following. Finally, the Globally Stable Sliding Mode (GSSM) control and Globally Stable Integral Sliding Mode S-Plane (GSISM S-Plane) control are used for a comparative experiment. The simulation results show that the designed GSISM+RBF S-Plane controller can accurately track the ideal path compared with the GSSM and GSISM S-Plane controller, and it has good control performance and anti-disturbance performance.

Fault‐tolerant attitude tracking control of tandem rotor helicopter considering internal actuator saturation and external wind gust

SummaryTandem rotor helicopter is configured with two main rotors distributed along the longitudinal direction and without anti‐torque tail rotor. Therefore, the control strategy of tandem rotor helicopter can be quite different from that of traditional helicopter systems. In this article, a fault‐tolerant attitude tracking controller is presented for tandem rotor helicopter, with considerations of external wind disturbance and internal actuator problem. First, attitude control oriented dynamic model of the tandem rotor helicopter is constructed, in which both actuator fault and saturation are involved. Base on statistical characteristics of practical wind condition as well as aerodynamic properties of the helicopter rotors, a detailed wind load model is further established. Then, a fault‐tolerant attitude tracking controller is proposed for the tandem rotor helicopter system by incorporating nonsingular terminal sliding mode control with an adaptive super twisting algorithm, which allows a simultaneous regulation of the three angular motions via two propeller rotors. Finally, based on Quanser's 3‐dof helicopter system, comparative simulation tests are performed to demonstrate the effectiveness as well as advantages of the proposed fault‐tolerant controller design.

Modeling and Control of Quadcopter Based on Sliding Mode Robust Control in the Wind Field

Due to the low flying height, quadrotors are easily affected by external wind disturbances. In this paper, the dynamic model of the quadrotor flying in the wind field is established according to the Newton-Euler equation. The model introduces a weight function due to the phenomenon that different rotors are affected differently by the wind field due to their different positions relative to the wind field, and a sliding mode robust controller based on inner and outer loops is designed. The verification of the control system is carried out by means of simulation in a Gazebo and actual flight experiments in the wind field. The dynamic of the system and the controller performance under the wind field are also tested. The results show that the designed controller has the performance of stable flight in the wind field environment.

Fault detection in wind turbine transmission systems via finite frequency observers

AbstractThis paper addresses fault detection for wind turbine transmission system (WTTS) subject to actuator stuck faults and wind disturbances. Taking into account the frequency domain characteristics of such faults and disturbances, a modified observer is designed in terms of finite frequency (FF) performance indices that have detection performances superior to some formerly proposed ones. With the generalized Kalman–Yakubovich–Popov (GKYP) lemma and the Lyapunov theory, the FF performance indices are related to linear matrix inequalities (LMIs), and parametrization of the corresponding FF modified observer is completed by convex optimization under LMI constraints. One typical advantage of the modified observer is that fault and disturbance signals in distinctive FF domains can be dealt with simultaneously. This makes the residual system sensitive to actuator stuck faults and robust against external wind disturbances. Simulations are included to show that the design method achieves fault detection performances better than those of the entire frequency observers.

Finite Time Trajectory Tracking with Full-State Feedback of Underactuated Unmanned Surface Vessel Based on Nonsingular Fast Terminal Sliding Mode

Marine transportation and operations have attracted the attention of more and more countries and scholars in recent years. A full-state finite time feedback control scheme is designed for the model parameters uncertainty, unknown ocean environment disturbances, and unmeasured system states in the underactuated Unmanned Surface Vessel (USV) trajectory tracking control. The external wind, wave and current environmental disturbances and model parameters perturbation are extended by Nonlinear Extended State Observer (NESO) to the state of the system, namely complex disturbances. The complex disturbances, positions and velocities of USV can be observed by NESO and feedback to USV control system. Next, the underactuated USV error model is obtained by operating the obtained feedback information and the virtual ship model. According to the error model, a Nonsingular Fast Terminal Sliding Model surface (NFTSM) is constructed to realize finite-time control. The control law is deduced through the Lyapunov stability theory to ensure the stability of the system. The results of MATLAB numerical simulations under different disturbances show that the trajectory tracking algorithm has fast responses, and a good convergence of the errors is observed, which verifies the effectiveness of the designed scheme.

Composite Filtering for UWB-Based Localization of Quadrotor UAV With Skewed Measurements and Uncertain Dynamics

Nowadays, the ultrawideband (UWB) has become a popular solution to the indoor localization problem of quadrotor unmanned aerial vehicle (UAV) due to its low power consumption and ease of implementation. Nonetheless, the accuracy of UAV localization is affected by the skew- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> measurement noises of the UWB sensor induced mainly by the nonline-of-sight (NLOS) errors and the multipath effects, and the uncertainties in the UAV dynamics caused by external wind disturbances. In this article, a composite filtering approach is proposed for time difference of arrival (TDOA)-based UWB localization of the quadrotor UAV. The main advantage of the composite filtering approach lies in its capability of dealing with the skew- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> measurement noises and the dynamic uncertainties simultaneously. Specifically, the external winds are estimated and rejected in real time via the disturbance observer (DO). Meanwhile, the posterior state distribution under skew- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> measurement noises is updated in an iterative fashion within the variational Bayes (VB) framework. The effectiveness of the proposed approach is validated through both numerical simulation and experimental tests on a quadrotor UAV.

Systematic Online Tuning of Multirotor UAVs for Accurate Trajectory Tracking Under Wind Disturbances and In-Flight Dynamics Changes

The demand for accurate and fast trajectory tracking for multirotor Unmanned Aerial Vehicles (UAVs) have grown recently due to advances in UAV avionics technology and application domains. In many applications, the multirotor UAV is required to accurately perform aggressive maneuvers in challenging scenarios like the presence of external wind disturbances or in-flight payload changes. In this paper, we propose a systematic controller tuning approach based on identification results obtained by a recently developed Deep Neural Networks with the Modified Relay Feedback Test (DNN-MRFT) algorithm. We formulate a linear equivalent representation suitable for DNN-MRFT using feedback linearization. This representation enables the analytical investigation of different controller structures and tuning settings, and captures the non-linearity trends of the system. With this approach, the trade-off between performance and robustness in design was made possible which is convenient for the design of controllers of UAVs operating in uncertain environments. We demonstrate that our approach is adaptive and robust through a set of experiments, where accurate trajectory tracking is maintained despite significant changes to the UAV aerodynamic characteristics and the application of wind disturbance. Due to the model-based system design, it was possible to obtain low discrepancy between simulation and experimental results which is beneficial for potential use of the proposed approach for real-time model-based planning and fault detection tasks. We obtained RMSE of 3.59 cm when tracking aggressive trajectories in the presence of strong wind, which is on par with state-of-the-art.