Automatic Landing Research Articles

Adaptive Prescribed Time Control Method for Automatic Carrier Landing System

To address the issue of the short landing time and high convergence speed requirements for carrier-based aircraft, an adaptive prescribed time control (APTC) method is proposed. This method combines adaptive technique to estimate and compensate for modeling uncertainties and disturbances in the landing system. It ensures custom-defined prescribed time convergence for glide path tracking errors, regardless of initial states and control parameters. The stability of the landing control method is proven using the Lyapunov function theorem. Based on this method, an Automatic Carrier Landing System (ACLS) for carrier-based aircraft is developed. Numerical simulation tests with different convergence times verify that the method can achieve custom-defined prescribed time convergence. Finally, by introducing the PID and traditional prescribed time control methods for comparison, the numerical results demonstrate that the proposed APTC method achieves faster convergence speed and higher convergence accuracy in landing trajectory tracking.

Automatic Landing Control for Fixed-Wing UAV in Longitudinal Channel Based on Deep Reinforcement Learning

The objective is to address the control problem associated with the landing process of unmanned aerial vehicles (UAVs), with a particular focus on fixed-wing UAVs. The Proportional–Integral–Derivative (PID) controller is a widely used control method, which requires the tuning of its parameters to account for the specific characteristics of the landing environment and the potential for external disturbances. In contrast, neural networks can be modeled to operate under given inputs, allowing for a more precise control strategy. In light of these considerations, a control system based on reinforcement learning is put forth, which is integrated with the conventional PID guidance law to facilitate the autonomous landing of fixed-wing UAVs and the automated tuning of PID parameters through the use of a Deep Q-learning Network (DQN). A traditional PID control system is constructed based on a fixed-wing UAV dynamics model, with the flight state being discretized. The landing problem is transformed into a Markov Decision Process (MDP), and the reward function is designed in accordance with the landing conditions and the UAV’s attitude, respectively. The state vectors are fed into the neural network framework, and the optimized PID parameters are output by the reinforcement learning algorithm. The optimal policy is obtained through the training of the network, which enables the automatic adjustment of parameters and the optimization of the traditional PID control system. Furthermore, the efficacy of the control algorithms in actual scenarios is validated through the simulation of UAV state vector perturbations and ideal gliding curves. The results demonstrate that the controller modified by the DQN network exhibits a markedly superior convergence effect and maneuverability compared to the unmodified traditional controller.

Four-stage cascaded adaptive sliding mode control for automatic carrier landing with airwake disturbances and uncertainties

ObjectiveThis paper addresses the carrier landing affected by airwake, parametric uncertainties, and carrier deck motion, its main target being the design of a novel sliding mode based automatic carrier landing system to obtain accurate tracking of the reference trajectory, robustness in terms of disturbances and uncertainties, as well as excellent touchdown accuracy. ApproachFor an aircraft nonlinear dynamics, written under a four-stage cascaded strict feedback form, the design of the novel landing control architecture involves the design of a guidance subsystem, robust sliding mode controllers (for the control of the heading angle, attitude angles, and angular rates), an approach power compensation system, adaptive control laws suppressing the uncertainties and disturbances, a Kalman filter for deck motion prediction, a block computing the reference trajectory, a tracking differentiator block for deck motion compensation, and first-order command filters. Main resultsThe software validation process proves the effectiveness of the sliding mode based control scheme and the suppression of the uncertainties and disturbances. Also, the comparison between the performances of the sliding mode control based carrier landing system and the ones associated to other automatic carrier landing systems shows the superiority of the sliding mode based control scheme, as well as its better touchdown accuracy and landing success rate. SignificanceThis study innovatively transforms the general carrier landing problem into a time-varying tracking control problem for cascaded strict feedback dynamics with disturbances and uncertainties. The new designed automatic carrier landing system is the first control architecture in the literature employing the sliding mode control augmented by adaptive control laws for carrier landing, subjected to airwake, deck motion, and uncertainties.

Are Modern Market-Available Multi-Rotor Drones Ready to Automatically Inspect Industrial Facilities?

Industrial inspection is a well-known application area for unmanned aerial vehicles (UAVs), but are modern market-available drones fully suitable for inspections of larger-scale industrial facilities? This review summarizes the pros and cons of aerial large-scale facility inspection, distinguishing it from other inspection scenarios implemented with drones. Moreover, based on paper analysis and additionally performed experimental studies, it reveals specific issues related to modern commercial drone software and demonstrates that market-available UAVs (including DJI and Autel Robotics) more or less suffer from the same problems. The discovered issues include a Global Navigation Satellite System (GNSS) Real Time Kinematic (RTK) shift, an identification of multiple images captured from the same point, limitations of custom mission generation with external tools and mission length, an incorrect flight time prediction, an unpredictable time of reaching a waypoint with a small radius, deviation from the pre-planned route line between two waypoints, a high pitch angle during acceleration/deceleration, an automatic landing cancellation in a strong wind, and flight monitoring issues related to ground station software. Finally, on the basis of the paper review, we propose solutions to these issues, which helped us overcome them during the first autonomous inspection of a 2400 megawatts thermal power plant.

Composite adaptive neural control for automatic carrier landing system with input saturation and output constraints

This paper investigates the automatic carrier landing control problem in the presence of model uncertainty, airwake disturbances, input saturation, and output constraints. Considering the performance requirements of the carrier-based aircraft, a composite adaptive neural controller is proposed based on the time-varying barrier Lyapunov function and backstepping control techniques. The radial basis function neural network is used to approximate the model uncertainty, where the neural network weight update law incorporating prediction and tracking errors further improves the convergence rate of the neural network and mitigates high-frequency oscillations. Furthermore, an adaptive disturbance compensation model is established to mitigate the adverse effects of airwake disturbances and estimation errors in the neural network. Based on the Lyapunov stability theory, it is proven that the proposed controller maintains the aircraft trajectory within the prescribed constraints and also ensures that all signals in the closed-loop control system are semiglobally uniformly ultimately bounded. Finally, comparative simulations are performed to demonstrate the effectiveness and superiority of the proposed composite adaptive neural control method.

Antisaturation fixed-time backstepping fuzzy integral sliding mode control for automatic landing of fixed-wing unmanned aerial vehicles

This paper proposes a robust adaptive fixed-time control for automatic landing systems (ALS) of small-scale fixed-wing UAVs exposed to wind disturbances, parametric uncertainties, and input saturation. The control structure consists of three subsystems, i.e., the guidance system, the attitude control system, and the thrust control system. Considering the landing geometry, the guidance system computes the desired Euler angles to stabilize the dynamics of altitude deviation, lateral deviation, and lateral speed. An auxiliary system is designed to compensate for the effect of input saturation in the attitude control system. The fixed-time method, the backstepping control (BSC), the fuzzy logic control (FLC), and the integral sliding mode control (ISMC) techniques are adopted to synthesize the control law. All three functional parts of the proposed ALS are equipped with a fixed-time fuzzy sliding mode disturbance observer (FSMDO). FLC computes the gains of signum functions adaptively to attenuate the chattering. Fixed-time convergence of the system errors to an arbitrary residual set is proved by comprehensive stability analysis. Finally, the comparative simulation results verify the better dynamic response and stronger robustness under the proposed ALS.

Adaptive terminal sliding combined super twisting control design and flight tests for automatic carrier landing system

Considering the challenges posed by external disturbances on carrier-based aircraft landing control, higher demands are required for the precision and convergence of the carrier landing control system. First, this paper proposes an Adaptive Terminal Sliding Combined Super Twisting Control (ATS-STC) method to address the issues of low precision, slow convergence, and poor disturbance rejection capability resulting from external disturbances, such as carrier air-wake and deck motion. By introducing a nonlinear term into the sliding surface and employing an integral approach, the proposed ATS-STC method can ensure finite-time convergence and mitigate the chattering problem. An adaptive law is also utilized to estimate the external disturbances, thereby enhancing the anti-disturbance performance. Then, the stability and convergence time analysis of the designed controller are conducted. Based on the proposed method, an Automatic Carrier Landing System (ACLS) is developed to perform the carrier landing control task. Furthermore, a multi-dimensional validation is carried out. For the numerical simulation test, the Terminal Sliding Mode Control (TSMC) method and Proportion Integration Differentiation (PID) method are introduced as comparison, the quantitative assessment results show that the tracking error of TSMC and PID can reach 1.5 times and 2 times that of the proposed method. Finally, the Hardware-in-the-Loop (HIL) test and real flight test are conducted. All the experimental results demonstrate that the proposed control method is more effective and precise.

Fruit fly optimization algorithm with escape predation mechanism based direct lift control for automatic carrier landing

This paper designs a practical automatic carrier landing system (ACLS) that utilizes direct lift control (DLC) technology, and the controller parameters are optimized by using the enhanced fruit fly optimization algorithm with escape predation mechanism (EPFOA). The designed ACLS comprises the control channels of elevator, flap and throttle. The coordinated action of the elevator and flap can generate direct lift, enabling the aircraft to approach the desired glide path quickly and accurately. A decoupling module is designed to enhance the attitude stability of the aircraft during landing, thereby increase the success rate of landing. In order to achieve the better control effectiveness, the EPFOA is proposed to optimize the controller parameters of the DLC-based ACLS. Inspired by the predator-escape behavior between dingoes and sheep, EPFOA divides the whole fruit fly swarm into three categories: discovered escaping fruit fly (DEF), escaping fruit fly (EF) and predator fruit fly (PF). The PFs can ensure the population of convergence, while the DEFs and EFs can preserve the diversity of the population and avoid falling into local optima. Experiments are conducted in various cases, and the designed DLC-ACLS demonstrates superior ability in flight path adjustment and attitude control compared to the traditional F/A-18 ACLS in landing control. Additionally, the proposed EPFOA shows superior performance compared to other optimization algorithms.

Robust fault-tolerant preview control for automatic landing of carrier-based aircraft

PurposeThis paper aims to propose the automatic carrier landing system with the fault-tolerant ability for carrier-based aircraft in the presence of deck motion, external airwake disturbance and actuator fault, which consists of the reference trajectory generation module and flight control module.Design/methodology/approachThe longitudinal and lateral basic controllers are designed based on the optimal preview control (OPC), which can ensure favorable tracking performance and anti-disturbance ability of system. Furthermore, based on the OPC, the robust fault-tolerant preview control scheme is proposed to attenuate the impact of actuator fault on system, which ensures the safe landing of carrier-based aircraft in case of actuator failure.FindingsBoth the Lyapunov method and simulations prove that the tracking errors can converge to zero and system states can be asymptotically stable both in normal and fault operations.Originality/valueThe fault-tolerant control strategy is introduced into preview control to deal with actuator fault, which combines feedforward control based on future previewable information and feedback control based on current information to improve the system performance.

Deck motion prediction using neural kernel network Gaussian process regression

Deck motion prediction and compensation are critical technologies for carrier-based aircraft automatic landing. Traditional deck motion prediction methods rely on precision of motion models and parameter adjustments, facing challenges in adaptability to complex sea conditions, different types of carriers, changes in flight conditions, and limitations in prediction duration, as well as reliability issues. This paper proposes a deck motion prediction method based on the neural kernel network Gaussian process regression (NKN-GPR) model. The NKN-GPR model can utilize a neural kernel network (NKN) to automatically construct the Gaussian process regression (GPR) model′s composite kernel, effectively addressing the limitations of the automated kernel search (ACKS) algorithm, which heavily depends on manual prior knowledge. Simulation data is generated using a combination of sine wave and power spectrum models, and the NKN-GPR model is compared with an autoregressive (AR) model based on least squares in a simulated validation. The simulation results demonstrate that the NKN-GPR model exhibits significant advantages in motion prediction accuracy, smoothness, and prediction duration, which confirms the effectiveness of the proposed algorithm. This study provides theoretical support for safe automatic landing of carrier-based aircraft.

Fault-tolerant control of automatic carrier landing using direct lift control based on nonsingular terminal sliding mode and active disturbance rejection control

This paper presents a fault-tolerant control scheme, combining nonsingular terminal sliding mode and active disturbance rejection control (NTSM-ADRC) to address actuator failure and external disturbances during the automatic carrier landing process of a carrier-based aircraft using direct lift control (DLC). First, the carrier-based aircraft model, the carrier air-wake model, and the actuator fault model were established. Second, the NTSM-ADRC controller is designed, The unmodeled dynamics of the system, the air-wake disturbance, and the fault term are treated as total disturbances and estimated accurately by extended state observer (ESO). To improve the response characteristics of the controller, the nonlinear error feedback control law is designed by combining the NTSMC. The Lyapunov function is constructed to prove the stability of the closed-loop system. The controller is applied to the aircraft DLC channel, attitude auxiliary channel, and approach power compensation system. The DLC improves the performance of fixed-wing aircraft by directly generating high lift through the flaps to change the aircraft trajectory. Finally, the method is tested by introducing various types of actuator failures. Simulation results demonstrate that the designed longitudinal fault-tolerant carrier landing system exhibits strong robustness and fault tolerance, thereby improving the accuracy of aircraft landing trajectory tracking.

Virtually constrained generalized relative motion modeling and a control parameter optimizer for automatic carrier landing

PurposeThis paper aims to propose a novel control scheme and offer a control parameter optimizer to achieve better automatic carrier landing. Carrier landing is a challenging work because of the severe sea conditions, high demand for accuracy and non-linearity and maneuvering coupling of the aircraft. Consequently, the automatic carrier landing system raises the need for a control scheme that combines high robustness, rapidity and accuracy. In addition, to exploit the capability of the proposed control scheme and alleviate the difficulty of manual parameter tuning, a control parameter optimizer is constructed.Design/methodology/approachA novel reference model is constructed by considering the desired state and the actual state as constrained generalized relative motion, which works as a virtual terminal spring-damper system. An improved particle swarm optimization algorithm with dynamic boundary adjustment and Pareto set analysis is introduced to optimize the control parameters.FindingsThe control parameter optimizer makes it efficient and effective to obtain well-tuned control parameters. Furthermore, the proposed control scheme with the optimized parameters can achieve safe carrier landings under various severe sea conditions.Originality/valueThe proposed control scheme shows stronger robustness, accuracy and rapidity than sliding-mode control and Proportion-integration-differentiation (PID). Also, the small number and efficiency of control parameters make this paper realize the first simultaneous optimization of all control parameters in the field of flight control.

Global fast terminal sliding mode control for automatic carrier landing with environmental disturbances

Purpose The purpose of this paper is to solve the challenging problem of automatic carrier landing with the presence of environmental disturbances. Therefore, a global fast terminal sliding mode control (GFTSMC) method is proposed for automatic carrier landing system (ACLS) to achieve safe carrier landing control. Design/methodology/approach First, the framework of ACLS is established, which includes flight glide path model, guidance model, approach power compensation system and flight controller model. Subsequently, the carrier deck motion model and carrier air-wake model are presented to simulate the environmental disturbances. Then, the detailed design steps of GFTSMC are provided. The stability analysis of the controller is proved by Lyapunov theorems and LaSalle’s invariance principle. Furthermore, the arrival time analysis is carried out, which proves the controller has fixed time convergence ability. Findings The numerical simulations are conducted. The simulation results reveal that the proposed method can guarantee a finite convergence time and safe carrier landing under various conditions. And the superiority of the proposed method is further demonstrated by comparative simulations and Monte Carlo tests. Originality/value The GFTSMC method proposed in this paper can achieve precise and safe carrier landing with environmental disturbances, which has important referential significance to the improvement of ACLS controller designs.

Fault-Tolerant Control for Carrier-Based Aircraft Automatic Landing Subject to Multiple Disturbances and Actuator Faults

This paper introduces a fault-tolerant control scheme for the automatic carrier landing of carrier-based aircraft using direct lift control. The scheme combines radial basis function neural network and active disturbance rejection control (RBF-ADRC) to overcome the impact of actuator failures and external disturbances. First, the carrier-based aircraft model, the carrier air-wake model, and the actuator fault model were established. Secondly, ADRC is designed to estimate and compensate for actuator faults and disturbances in real time. RBFNN adjusts the ADRC controller parameters based on the system state. Then, the Lyapunov function is constructed to prove the stability of the closed-loop system. The controller is applied to the direct lift control channel, auxiliary attitude channel, and approach power compensation system. The direct lift control improves the performance of fixed-wing aircraft. Finally, comparative simulations were conducted under various actuator failures. The results demonstrate the remarkable fault tolerance of the RBF-ADRC scheme, enabling precise tracking of the desired glide path by the shipboard aircraft even in the presence of actuator failures.

Study of on-board equipment of modern uavs

This paper analyzes the development and production of modern unmanned aerial vehicles (UAVs). It is noted that they have the following main systems: glider; propulsion system; power supply system; management system; navigation system; telemetry system; radio communication system. All UAV systems are interconnected and work as one complex mechanism. Depending on the list of combat tasks to be solved, the following devices can be additionally installed on board the UAV: optical-electronic, thermal imaging, radar, radiotechnical, radiation, chemical, bacteriological and other types of reconnaissance systems with small intelligence storage systems; means of setting active radio-electronic jammers; means of aiming and adjusting guided weapons; various means of defeat; means of control and communication with the ground control point; responsible for the state identification system; autonomous flight and automatic landing devices. The work reveals the features of the UAV engine design, it is noted that 4, 6 or more engines are installed on modern helicopter-type UAVs, so-called "multicopters", "quadracopters", "drones". In this work, it is noted that the UAV navigation equipment can have various level of complexity and use several signals coming from sensors of different physical origins to calculate its location. The features of the UAV radio communication system are revealed, which is a set of various lines through which intelligence information of various levels of importance and protection is transmitted. All communication links can use different frequency bands and different relay modes, use different signal-code designs, specially adapted to the importance of the intelligence information being transmitted. It was noted that in the absence of a control command, the UAV goes into autonomous flight mode.

GPS-Free Wireless Precise Positioning System for Automatic Flying and Landing Application of Shipborne Unmanned Aerial Vehicle.

This research is dedicated to developing an automatic landing system for shipborne unmanned aerial vehicles (UAVs) based on wireless precise positioning technology. The application scenario is practical for specific challenging and complex environmental conditions, such as the Global Positioning System (GPS) being disabled during wartime. The primary objective is to establish a precise and real-time dynamic wireless positioning system, ensuring that the UAV can autonomously land on the shipborne platform without relying on GPS. This work addresses several key aspects, including the implementation of an ultra-wideband (UWB) circuit module with a specific antenna design and RF front-end chip to enhance wireless signal reception. These modules play a crucial role in achieving accurate positioning, mitigating the limitations caused by GPS inaccuracy, thereby enhancing the overall performance and reception range of the system. Additionally, the study develops a wireless positioning algorithm to validate the effectiveness of automatic landing on the shipborne platform. The platform's wave vibration is considered to provide a realistic landing system for shipborne UAVs. The UWB modules are practically installed on the shipborne platform, and the UAV and the autonomous three-body vessel are tested simultaneously in the outdoor open water space to verify the functionality, precision, and adaptability of the proposed UAV landing system. Results demonstrate that the UAV can autonomously fly from 200 m, approach, and automatically land on the moving shipborne platform without relying on GPS.

Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints

Iterative Model Predictive Control for Automatic Carrier Landing of Carrier-Based Aircrafts Under Complex Surroundings and Constraints

Charging Between PADs: Periodic Charging Scheduling in the UAV‐Based WRSN With PADs

Wireless rechargeable sensor network (WRSN) has become the most effective solution to the energy problem in wireless sensor networks (WSNs) by introducing mobile chargers (MCs) to replenish energy for energy‐starved sensor nodes. In the studies of WRSN, there has been growing interest in using lightweight unmanned aerial vehicles (UAVs) as MCs to overcome geographical constraints. Recently, automatic landing pads (PADs) have been introduced in the UAV‐based WRSN, enabling the UAV to automatically replenish energy during the charging flight. Consequently, the UAV’s service range is enlarged, and the UAV can now perform large‐scale charging services. In this paper, we investigate the periodic charging scheduling problem in this novel form of WRSN with the goal of minimizing the charging delay. We present the problem’s definition and model and prove it is NP‐hard. To address this problem, we propose two periodic charging schemes: SNBC (sensor‐node‐based charging scheme) and PBC (PAD‐based charging scheme). We extensively simulated our proposed schemes in a UAV‐based WRSN with PADs, evaluating them based on two key metrics: charging delay and UAV replenishment frequency. The results indicate the efficiency of our approaches. SNBC averaged a 7.2 × 104 s charging delay, while PBC outperformed it with a 14.01% reduction in charging delay and a 13.66% decrease in replenishment frequency.

Application of linguistic fuzzy neural network to landing control

Most aircraft accidents occurred during the final approach. Wind disturbance is one of the significant factors in these accidents. During the landing phase, the Automatic Landing System (ALS) can help aircraft land safely and significantly reduce the pilot’s work loading. Control schemes of the conventional ALS usually use gain-scheduling and traditional PID control techniques. A traditional controller cannot control the aircraft if the weather conditions are beyond the allowed limits. To improve the performance of the landing control, this study applies a linguistic fuzzy neural network (LFNN) to replace the conventional controller of ALS. Adaptive learning rules are proposed to enhance the LFNN control ability. The method used to obtain adaptive learning rules is the Lyapunov stability theory. Moreover, the convergence of the system performance error is proved by the Lyapunov theory. This study also compares previously proposed control schemes in aircraft landing control. Different turbulence strengths are implemented into the flight simulation to make the proposed controller more robust and adaptive to various wind disturbance conditions. The LFNN controller can successfully overcome 75 ft/s wind speed, while the adaptive LFNN can reach 80 ft/s with optimal learning rates. Using optimal convergence theorems, the proposed controller performs better than the controllers trained by a fixed learning rate.

Modeling the influence of external influences on the process of automated landing of a UAV-quadcopter on a moving platform using technical vision

This article describes a series of experiments in the Gazebo simulation environment aimed at studying the influence of external weather conditions on the automatic landing of an unmanned aerial vehicle (UAV) on a moving platform using computer vision and a previously developed control system based on PID and polynomial controllers. As part of the research, methods for modeling external weather conditions were developed and landing tests were carried out simulating weather conditions such as wind, light, fog and precipitation, including their combinations. In all experiments, successful landing on the platform was achieved; during the experiments, landing time and its accuracy were measured. The graphical and statistical analysis of the obtained results revealed the influence of illumination, precipitation and wind on the UAV landing time, and the introduction of wind into the simulation under any other external conditions led to the most significant increase in landing time. At the same time, the study failed to identify a systemic negative influence of external conditions on landing accuracy. The results obtained provide valuable information for further improvement of autonomous automatic landing systems for UAVs without the use of satellite navigation systems.