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The paper studies the control problem of an uncertain nonlinear system with tracking error constraint, unknown nonlinear functions and unknown control input gains. An asymmetric barrier Lyapunov function composed with predefined time prescribed performance function is constructed to ensure tracking error enters into the predefined asymmetric constraint in a given time. Then radial basis function neural network is adopted to approximate unknown functions. To reduce computation load, minimal-learning parameter technique is applied. Meanwhile, adaptive method is used to solve actuator faults and the unknown control input gains. Moreover, an adaptive neural control strategy is designed in the framework of backstepping method. An adaptive fixed time filter is developed for avoiding the "explosion of complexity" problem, where the convergence speed of the filter error is improved compared with fixed time filter. It is proved that all signals of the closed-loop system are bounded and tracking error is kept in its constraint boundary. At the end, compared numerical simulations and application simulation of a hypersonic vehicle are demonstrated to verify the efficiency of the designed control scheme. • A composed performance function is designed to ensure the tracking error enters into the constraint in a given time. • An adaptive fixed time filter is developed to solve the 'explosion of complexity' problem. • Based on minimal-learning parameter method, neural networks estimate unknown functions, which reduce computation load. • Compared simulation and application simulation of a hypersonic vehicle are given to test the efficiency of the controller. [ABSTRACT FROM AUTHOR]

This paper proposes a novel, robust flight control system using adaptive nonlinear sliding mode control for a quadrotor UAV in the presence of parametric uncertainties and aerodynamical disturbances. The proposed control system is based on a proportional derivative sliding surface combined with a non-singular fast terminal sliding mode control to enhance the tracking accuracy and reduce the chattering influence. Moreover, an adaptive mechanism is proposed to approximate the unknown upper limit of external disturbances/uncertainties. The Lyapunov criteria is used to prove the closed-loop stability and calculate the adaptive mechanism. The proposed adaptive PD-NFTSMC (APD-NFTSMC) can cope with the negative influence of modeling uncertainties, external disturbances, and measurement noise, allows null error in the steady state, and solves the chattering problem. Moreover, intensive simulation experiments under various external conditions are carried out to highlight the sovereignty of the developed control approach. Finally, comparisons with some well-known control techniques are performed to show the usefulness, smoothness, and robustness of the proposed APD-NFTSMC strategy. [ABSTRACT FROM AUTHOR]

This paper presents an active fault-tolerant flight control system (FCS) design for the dual-system/hybrid VTOL UAV configuration that maximally exploits its inherent over-actuation abilities to provide higher levels of fault-tolerance and reliability compared to that of the other VTOL UAVs configurations up to this point. The significance of this study is to convert the main drawback of having the vertical rotors as dead weights during the cruise to a key advantage where all the UAV's controls are kept active during all the flight phases raising the UAV's fault-tolerance and maneuverability abilities. The FCS proposed elaborates on a new architecture for the hierarchical automatic control loops using the dynamic inversion control to design the trajectory tracking virtual commands and employing optimal dynamic control allocation to optimally resolve the controls redundancy. Regarding fault-tolerance, the presented FCS handles simultaneous failures and jamming of all the control surfaces during flight where the control commands to the healthy controls (vertical rotors) were automatically adapted such that the trimming and trajectory tracking were successfully maintained till the mission end. Additionally, this paper addresses for the first time the employment of the controls redundancy to enhance the VTOL UAV's maneuverability in fault-free cases, where we present a study of reducing the minimum turn radius of the UAV when the vertical rotors are employed with the control surfaces during the maneuver. A reduction of 38% in the coordinated steady-level minimum turn radius turn at 35 m/sec flight speed was achieved. [ABSTRACT FROM AUTHOR]

The development of complex equipment has the feature of "main manufacturer-supplier", with a large amount of underlying data and a small amount of top-level data for reliability growth. This paper firstly introduces the basic model of reliability growth. For small samples and uncertain of complex equipment, Bayesian methods and grey system theory have also been investigated. It has been found that existing research cannot describe this distributed collaborative network and the inherent mechanism of reliability growth, and the information data of reliability growth had not been fully utilized. This paper proposes a new model that combines Bayesian and GERT networks. This model is suitable for evaluating the reliability growth process in collaborative development networks, and can make full use of supplier information, historical information, and experimental information to comprehensively evaluate the reliability growth. Through case analysis of the flight control system, it is proven that the new model performs well in comprehensively utilizing various types of information. [ABSTRACT FROM AUTHOR]

Purpose: This research study aims to minimize autonomous flight cost and maximize autonomous flight performance of a slung load carrying rotary wing mini unmanned aerial vehicle (i.e. UAV) by stochastically optimizing autonomous flight control system (AFCS) parameters. For minimizing autonomous flight cost and maximizing autonomous flight performance, a stochastic design approach is benefitted over certain parameters (i.e. gains of longitudinal PID controller of a hierarchical autopilot system) meanwhile lower and upper constraints exist on these design parameters. Design/methodology/approach: A rotary wing mini UAV is produced in drone Laboratory of Iskenderun Technical University. This rotary wing UAV has three blades main rotor, fuselage, landing gear and tail rotor. It is also able to carry slung loads. AFCS variables (i.e. gains of longitudinal PID controller of hierarchical autopilot system) are stochastically optimized to minimize autonomous flight cost capturing rise time, settling time and overshoot during longitudinal flight and to maximize autonomous flight performance. Found outcomes are applied during composing rotary wing mini UAV autonomous flight simulations. Findings: By using stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads over previously mentioned gains longitudinal PID controller when there are lower and upper constraints on these variables, a high autonomous performance having rotary wing mini UAV is obtained. Research limitations/implications: Approval of Directorate General of Civil Aviation in Republic of Türkiye is essential for real-time rotary wing mini UAV autonomous flights. Practical implications: Stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads is properly valuable for recovering autonomous flight performance cost of any rotary wing mini UAV. Originality/value: Establishing a novel procedure for improving autonomous flight performance cost of a rotary wing mini UAV carrying slung loads and introducing a new process performing stochastic optimization of AFCS for rotary wing mini UAVs carrying slung loads meanwhile there exists upper and lower bounds on design variables. [ABSTRACT FROM AUTHOR]

This paper investigates a problem of autonomous aerial refueling point parallel rendezvous guidance and flight control subject to exogenous wind field disturbances. The tanker and uncrewed receiver aircraft approach the common refueling rendezvous point according to their respective flight plans, ultimately maintaining a fixed altitude and the same speed. According to the relative position of refueling target point and uncrewed receiver, a new continuous terminal sliding-mode guidance law combined with the prescribed performance control theory is designed under the end angle and speed constraints. Meanwhile, a finite-time observer is proposed to estimate the parameter uncertainties and wake vortex disturbances during refueling rendezvous. Based on the estimated information, a backstepping double-integral sliding-mode controller is developed for the uncrewed receiver flight control system. In the process of the guidance and flight control system, the integral variable is introduced to improve the steady-state performance. The designed guidance and control system can enable the uncrewed receiver to achieve the refueling rendezvous task within finite time and improve the efficiency of uncrewed aerial refueling. Comparative numerical simulations are provided to demonstrate the effectiveness of the proposed guidance and control scheme. [ABSTRACT FROM AUTHOR]

Gaining the ability to fly actively was a ground-breaking moment in insect evolution, providing an unprecedented advantage over other arthropods. Nevertheless, active flight was a costly innovation, requiring the development of wings and flight muscles, the provision of sufficient energetic resources, and a complex flight control system. Although wings, flight muscles, and the energetic budget of insects have been intensively studied in the last decades, almost nothing is known regarding the flight-control devices of many crucial insect groups, especially beetles (Coleoptera). Here, we conducted a phylogenetic-informed analysis of flight-related mechanosensors in 28 species of bark beetles (Curculionidae: Scolytinae, Platypodinae), an economically and ecologically important group of insects characterized by striking differences in dispersal abilities. The results indicated that beetle flight apparatus is equipped with different functional types of mechanosensors, including strain- and flow-encoding sensilla. We found a strong effect of allometry on the number of mechanosensors, while no effect of relative wing size (a proxy of flight investment) was identified. Our study constitutes the first step to understanding the drivers and constraints of the evolution of flight-control devices in Coleoptera, including bark beetles. More research, including a quantitative neuroanatomical analysis of beetle wings, should be conducted in the future. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to improve autonomous flight performance of a fixed-wing unmanned aerial vehicle (UAV) via simultaneous morphing wingtip and control system design conducted with optimization, computational fluid dynamics (CFD) and machine learning approaches. Design/methodology/approach: The main wing of the UAV is redesigned with morphing wingtips capable of dihedral angle alteration by means of folding. Aircraft dynamic model is derived as equations depending only on wingtip dihedral angle via Nonlinear Least Squares regression machine learning algorithm. Data for the regression analyses are obtained by numerical (i.e. CFD) and analytical approaches. Simultaneous perturbation stochastic approximation (SPSA) is incorporated into the design process to determine the optimal wingtip dihedral angle and proportional-integral-derivative (PID) coefficients of the control system that maximizes autonomous flight performance. The performance is defined in terms of trajectory tracking quality parameters of rise time, settling time and overshoot. Obtained optimal design parameters are applied in flight simulations to test both longitudinal and lateral reference trajectory tracking. Findings: Longitudinal and lateral autonomous flight performances of the UAV are improved by redesigning the main wing with morphing wingtips and simultaneous estimation of PID coefficients and wingtip dihedral angle with SPSA optimization. Originality/value: This paper originally discusses the simultaneous design of innovative morphing wingtip and UAV flight control system for autonomous flight performance improvement. The proposed simultaneous design idea is conducted with the SPSA optimization and a machine learning algorithm as a novel approach. [ABSTRACT FROM AUTHOR]

In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown terms, providing information for the disturbance observer. Besides, the tuning parameters are chosen optimally by adopting the grey wolf optimization (GWO) algorithm. The closed-loop system stability is also proven by the barrier Lyapunov function (BLF) while the total uncertainties, including system dynamics, friction, and disturbance, are tracked by the total estimation. Thus, the predetermined performance, robust behavior, and high-precision estimation are the achievements of the presented controller for PTS. To confirm the ability of the proposed control idea, simulations are provided. Furthermore, a comparison scenario is also considered to emphasize the supremacy of the proposed control system. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters. Design/methodology/approach: A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations. Findings: Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance. Research limitations/implications: Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights. Practical implications: Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index. Social implications: Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators. Originality/value: Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea. [ABSTRACT FROM AUTHOR]

A helicopter is a multivariable, nonlinear, higher order and strongly coupled system. The helicopter dynamics is subjected to unknown external disturbances and sensitive to parametric uncertainties. Such complications require a sophisticated control approach which may handle all these difficulties. The paper presents a trajectory control approach using an improved teaching learning based optimization (iTLBO) method, which optimizes the parameters of proportional integral derivative controller. This control approach is validated by minimizing the yaw and pitch errors of two degrees of freedom helicopter system. It is observed that the experimental results in a laboratory setup does not stand true when subjected to weather changes during the helicopter flight. To overcome this situation, a real time like conditions are created in the laboratory using the two external fans creating strong wind disturbance and the proposed controller is implemented to eliminate the resulting external disturbances created due to high speed wind of external fans. Initially, modelling of helicopter system is achieved using the Lagrangian approach. Then, the TLBO is tuned to improve the controller performance using MATLAB platform. The effectiveness and superiority of iTLBO is proved over other optimization techniques available in literature like GA, PSO and TLBO by using linear and nonlinear benchmark functions. The optimized parameters hence obtained are implemented on helicopter system under the presence of external air disturbance and disturbance less results are obtained. Results obtained are validated using time response analysis on the MATLAB/Simulation platform. [ABSTRACT FROM AUTHOR]

The flight control system for reusable launch vehicles has to work for an extensive flight envelope ranging from hypersonic to subsonic Mach numbers. Since the plant dynamics are highly nonlinear, time-varying, and coupled, classical controllers are designed for large stability margins about the linearised points. This limits the performance of the classical controller, and the design process is iterative and time-consuming. Hence adaptive controllers are designed to handle such complex systems using a standard quadratic Lyapunov function. The existing parameter update laws of the model reference adaptive control system are not robust to bounded disturbances and unmodelled dynamics. Hence this paper proposes modified controller parameter update laws using a rectangular projection operator and barrier Lyapunov function, ensuring robustness to structured and unstructured uncertainties. The rectangular projection-based control law provides that the controller parameters remain within the specified upper and lower limits, whereas the barrier Lyapunov-based controller maintains the trajectory also within the specified error limit. The effectiveness of the proposed update laws is demonstrated for the automatic landing phase of a reusable launch vehicle. [ABSTRACT FROM AUTHOR]

The need for reliable, fast, and accurate detection of fault is the key to fault-tolerant control reconfiguration of any flight control system. It is known that faults such as structural damage greatly modify the aerodynamic characteristics, often represented by stability and control derivatives. They also result in abrupt deterioration of flight performance and handling quality, which impairs safety. Since no detection technique is as reliable and fast as the Human Visual System (HVS), this paper demonstrates how popular vision algorithms such as edge detection and structural similarity index can be used for real-time detection of vertical tail damage of a fighter aircraft. A novel geometric method is proposed for fault identification using traditional mathematical geometry. Empirical techniques are used for the estimation of stability and control derivatives to generate a mathematical model of damaged aircraft instead of relying on expensive wind tunnel data. Flight mechanics analysis of the data generated confirms the effects of vertical damage in terms of reduction of static and dynamic directional stability and its control effectiveness. The parametrized state matrix thus obtained for the given flight condition thus leads to efficient real-time control reconfiguration of a damaged aircraft for safe recovery. The importance of this paper lies in using the established techniques of image processing for fault detection of damaged aircraft and parametrization for subsequent control reconfiguration, which is a novel application. [ABSTRACT FROM AUTHOR]

In this paper, the problem of closed-loop intermittent sensor fault (ISF) detection is investigated for a class of linear stochastic time-delay systems with unknown disturbances. A modified unknown input observer (UIO) is proposed to eliminate the influence of delayed errors caused by the discrete-time proportional-integral controller and constant time delay. In order to detect the appearing time and disappearing time of the ISF, a truncated residual is designed by introducing a sliding-time window. Moreover, two hypothesis tests are utilised to set the ISF detection thresholds, and the detectability, false alarm rates as well as missing alarm rates of the ISF are analysed in the framework of statistical analysis. Finally, the effectiveness of the proposed method is validated via a simulation example of a simplified radial flight control system. [ABSTRACT FROM AUTHOR]

This paper proposed a method for the reliability analysis of systems characterized by fuzzy failure probabilities and intricate failure behaviors, while retaining the fuzzy information throughout the analysis process. Specifically, we introduced a combinational modeling method that integrates generalized stochastic Petri nets (GSPN) and dynamic fault trees (DFT) to capture the dynamic failure behaviors and address the limitations of DFT modeling. This combinational approach is capable of capturing more sophisticated failure behaviors, such as competing failures and global failure propagation patterns. Furthermore, we propose an Monte Carlo technique based on endpoint sampling to enable quantitative analysis of GSPN‐based composite models, which preserves the fuzzy fault information of the system. Finally, we demonstrate the effectiveness of the proposed method through an example of a flight control system. [ABSTRACT FROM AUTHOR]

Automatic flight control system （AFCS） is one of the most important safety‑critical systems in modern aircraft, and flight guidance control system （FGCS） is an important part of it. There are dozens of flight modes in FGCS, and its mode conversion logic is very complex, which is prone to pattern confusion and other problems in the conversion of various modes, making it difficult to verify their safety and correctness. However, formal modeling and verification of safety‑critical systems can improve the correctness and safety of the system by using formal methods in computer science. This paper takes the automatic flight mode conversion logic of typical FGCS as the research object, uses the software tool ART （Avionics requirement tool） independently developed by the author team to carry out formal modeling and verification, and compares the verification ability and efficiency with the Design Verifier tool in Matlab/Simulink. The case study results show that it is feasible to model and verify the automatic flight mode conversion logic of FGCS using formal methods. Meanwhile, our software platform has more complete verification capability and better verification efficiency. [ABSTRACT FROM AUTHOR]

A rice vortex generated by the downwash airflow of the agricultural UAV has a great connection to pesticide droplet deposition. In this study, an unmanned aircraft system (UAS) was designed to obtain rice vortex parameters including position coordinates, area, and relative distance to the UAV. The system uses the flight control system mounted Beidou RTK positioning system and Manifold onboard computer to localize the spraying UAV and trains a YOLOv3-tiny model to recognize motion images of dynamic rice vortices in real-time, achieving a mean accuracy of 98.15% with 0.9326 IOU. Moreover, to optimize the system, a data time axis alignment method based on the robot operating system (ROS) was proposed to alleviate the transmission delay and image processing time-consumption, which increased the accuracy of the vortex parameter by 3.48%. The rice vortex area acquired by the UAS was highly relevant to UAV flight parameters and the relative distance was just correlated to the UAV height. The instantaneous status of the rice vortex helps to lay a data foundation for adjusting the flight parameters of the plant protection UAV. [ABSTRACT FROM AUTHOR]

Purpose: This study presents an image processing algorithm capable of calculating selected flight parameters requested by flight control systems to guide aircraft along the horizontal projection of the landing trajectory. The parameters identified based on the basics of the image of the Calvert light system appearing in the on-board video system are used by flight control algorithms that imitate the pilot's schematics of control. Controls were generated using a fuzzy logic expert system. This study aims to analyse an alternative to classical solutions that can be applied to some specific cases. Design/methodology/approach: The paper uses theoretical discussions and breakdowns to create the basics for the development of structures for both image processing algorithms and control algorithms. An analytical discussion on the first stage was transformed into laboratory rig tests using a real autopilot unit. The results of this research were verified in a series of software-in-the-loop computer simulations. Findings: The image processing method extracts the most crucial parameters defining the relative position of the aircraft to the runway, as well as the control algorithm that uses it. Practical implications: In flight control systems that do not use any dedicated ground or satellite infrastructure to land the aircraft. Originality/value: This paper presents the original approach of the author to aircraft control in cases where visual signals are used to determine the flight trajectory of the aircraft. [ABSTRACT FROM AUTHOR]

This work presents the comparative study among pole-placement (PP), optimal-control using output-feedback (OCOF), linear-quadratic regulator (LQR), and PID controllers for the twin rotor multi-input multi-output system (TRMS). The pitch and yaw are key attributes for stabilizing the TRMS MIMO system and control of flight. The main objective of this study is to use these classical controller techniques to monitor the pitch and yaw angles of TRMS and show the result of these techniques. Simulation results depicts the actual performance and reveals how PP outperforms the other techniques. [ABSTRACT FROM AUTHOR]

To make an all-electric aircraft possible, both high power densities and efficiencies are needed. However, particularly high demands are also placed on the thermal management system. Often, the electric motor and cooling system are considered without co-optimization. Particularly in the case of electric motors with conductors directly cooled by a liquid, there is great potential for optimization, since the temperature-dependent Joule losses determine the largest part of the losses. This publication shows the main influencing parameters for the electric motor and cooling system: coolant speed and winding temperature. In addition, the influence of the cooling system control during a flight mission is demonstrated and its potential in mass reduction is quantified. It could be shown that with a low utilized electric motor the maximum winding temperature of 130 ° C is beneficial, the cooling system should work in almost all operation points in its sized operation and the mass of the heat exchanger and pump is negligible compared to the mass of the electric motor and energy storage. [ABSTRACT FROM AUTHOR]

CONTROLLABLE ROTARY FLUID DAMPER (CRFD) is an efficient and cheap energy dissipation device, which is used to reduce the impact of vibration in mechanical systems. In this paper, the CRFD controlled by a servo motor is developed to reduce the effects of vibrations in the helicopter flight control system. The dynamic mechanical characteristic of the CRFD is experimentally investigated by the MTS machine. Due to the complex factors such as high shear thinning rate and compressibility of the damping medium, inertia of moving parts and internal friction, the CRFD studied has highly nonlinear hysteresis characteristics. The accuracy of the damper modeling is of great significance for designing effective vibration reduction methods. Therefore, a new generalized viscous-nonlinear elastic model is proposed to track the mechanical characteristics of CRFD. On the basis of parameter sensitivity analysis, the proposed generalized viscous-nonlinear elastic model is modified. According to the identification results of the modified model, the main parameters are fitted as polynomial functions of motor rotation angle. Through error analysis between analytical torques and experimental torques, it is concluded that the modified generalized viscous-nonlinear elastic model has the smallest error compared with Kwok and Maxwell models, which indicates that the proposed modified model can accurately describe the mechanical characteristics of the CRFD under different working conditions. [ABSTRACT FROM AUTHOR]

Flying insects exhibit outperforming stability and control via continuous wing flapping even under severe disturbances in various conditions of wind gust and turbulence. While conventional linear proportional derivative (PD)-based controllers are widely employed in insect-inspired flight systems, they usually fail to deal with large perturbation conditions in terms of the 6-DoF nonlinear control strategy. Here we propose a novel wing kinematics-based controller, which is optimized based on deep reinforcement learning (DRL) to stabilize bumblebee hovering under large perturbations. A high-fidelity Open AI Gym environment is established through coupling a CFD data-driven aerodynamic model and a 6-DoF flight dynamic model. The control policy with an action space of 4 is optimized using the off-policy Soft Actor–Critic (SAC) algorithm with automating entropy adjustment, which is verified to be of feasibility and robustness to achieve fast stabilization of the bumblebee hovering flight under full 6-DoF large disturbances. The 6-DoF wing kinematics-based DRL control strategy may provide an efficient autonomous controller design for bioinspired flapping-wing micro air vehicles. [ABSTRACT FROM AUTHOR]

Flight mills are widely used to investigate insect flight behavior. As technology advances, the means to build a computerized control system for a flight mill has become more accessible in terms of both price and availability of components. However, the specialized electronics and programming knowledge required to build such a system can still present an obstacle to interested parties. Here, we describe a simple and inexpensive flight mill control system that can be easily assembled and operated without specialized experience. The hardware and software components are built around an Arduino single-board microcontroller, which outputs raw data in the form of timestamped detections of rotations of the flight mill arm. This control system is suitable both as the basis for new flight mills and for replacing outdated computer controls on existing flight mills. Additionally, it can be used with any rotary flight mill design that uses an electronic sensor to count rotations. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to improve autonomous flight performance of an unmanned aerial vehicle (UAV) having actively sweep angle morphing wing using simultaneous UAV and flight control system (FCS) design. Design/methodology/approach: An UAV is remanufactured in the ISTE Unmanned Aerial Vehicle Laboratory. Its wing sweep angle can vary actively during flight. FCS parameters and wing sweep angle are simultaneously designed to optimize autonomous flight performance index using a stochastic optimization method called as simultaneous perturbation stochastic approximation (SPSA). Results obtained are applied for flight simulations. Findings: Using simultaneous design process of an UAV having actively sweep angle morphing wing and FCS design, autonomous flight performance index is maximized. Research limitations/implications: Authorization of Directorate General of Civil Aviation in Turkey is crucial for real-time UAV flights. Practical implications: Simultaneous UAV having actively sweep angle morphing wing and FCS design process is so beneficial for recovering UAV autonomous flight performance index. Social implications: Simultaneous UAV having actively sweep angle morphing wing and FCS design process achieves confidence, high autonomous performance index and simple service demands of UAV operators. Originality/value: Composing a novel approach to improve autonomous flight performance index (e.g. less settling and rise time, less overshoot meanwhile trajectory tracking) of an UAV and creating an original procedure carrying out simultaneous UAV having actively sweep angle morphing wing and FCS design idea. [ABSTRACT FROM AUTHOR]

Although drone users have received the necessary training, the reflexes of making decisions against a sudden natural event such as wind and avoiding a nearby obstacle may not be sufficient. Therefore, whether drones fly autonomously or under user control, they must sense and act accordingly for an uninterrupted mission. In this study, a drone design and application for obstacle detection and obstacle avoidance were carried out. In the designed drone, Pixhawk was used as the flight control board, ultrasonic sensors were used to detect obstacles, and Arduino Uno was used as a microcontroller to obtain avoidance commands. The sensors used in obstacle detection and their performance are the most decisive factors in achieving the targeted goal. Because obstacle detection sensors are affected by electrical noises, the success of detecting obstacles decreases. For this reason, first of all, the integration of these sensors into the system was investigated and the drone was developed accordingly. Then, an algorithm was developed using a software filtering method both to minimize communication instabilities and to increase the clarity of detection. Finally, the ability to evade obstacles both while the drone is suspended in the air and while it is in motion has been investigated. In the experiments carried out, it was found that the drone was able to successfully avoid obstacles up to a flight speed of 3.94 m/s [ABSTRACT FROM AUTHOR]

Purpose: This new paper aims to combine the recent new contributions about direct data driven control and other safety property to form an innovative direct data driven safety control for aircraft flight system. More specifically, within the framework of direct data driven strategy, the collected data are dealt with to get the identified plant and designed controller. After reviewing some priori information about aircraft flight system, a closed loop system with the unknown plant and controller simultaneously is considered. Data driven estimation is proposed to identify the plant and controller only through the ratios of two correlation functions, computed from the collected data. To achieve the dual missions about perfect tracking and safety property, a new notion about safety controller is introduced. To design this safety controller, direct data driven safety controller is proposed to solve one constrain optimization problem. Then the authors apply the Karush–Kuhn–Tucker (KKT) optimality conditions to derive the explicit safety controller. Design methodology approach: First, consider one closed loop system corresponding to aircraft flight system with the unknown plant and feed forward controller, data driven estimation is used to identify the plant and feed forward controller. This identification process means nonparametric estimation. Second, to achieve the perfect tracking one given transfer function and guarantee the closed loop output response within one limited range simultaneously, safety property is introduced. Then direct data driven safety control is proposed to design the safety controller, while satisfying the dual goals. Third, as the data driven estimation and direct data driven safety control are all formulated as one constrain optimization problem, the KKT optimality conditions are applied to obtain the explicit safety controller. Findings: Some aircraft system identification and aircraft flight controller design can be reformulated as their corresponding constrain optimization problems. Then through solving these constrain optimization problems, the optimal estimation and controller are yielded, while satisfying our own priori goals. First, data driven estimation is proposed to get the rough estimation about the plant and controller. Second, data driven safety control is proposed to get one safety controller before our mentioned safety concept. Originality/value: To the best of the authors' knowledge, some existing theories about nonparametric estimation and tube model predictive control are very mature, but few contributions are applied in practice, such as aircraft system identification and aircraft flight controller design. This new paper shows the new theories about data driven estimation and data driven safety control on aircraft, being corresponded to the classical nonparametric estimation and tube model predictive control. Specifically, data driven estimation gives the rough estimations for the aircraft and its feed forward controller. Furthermore, after introducing the safety concept, data driven safety control is introduced to achieve the desired dual missions with the combination of KKT optimality conditions. [ABSTRACT FROM AUTHOR]

Real‐time automated drone‐based crack detection can be used for efficient building damage assessment. This paper proposes an automated real‐time crack detection method based on a drone. Using a lightweight classification algorithm, a lightweight segmentation algorithm, a high‐precision segmentation algorithm, and a crack width measurement algorithm, the cracks are classified, roughly segmented, finely segmented, and the maximum width is extracted. A crack information‐assisted drone flight automatic control algorithm for automatic crack detection guides the drone toward the crack position. The effectiveness of the crack detection algorithm and the crack information‐assisted drone flight automatic control algorithm was tested on two different datasets, a two‐story building, and a 16‐m‐high shaking table test building. The results show that crack detection can be finished in real‐time during the flight. Using the proposed method can significantly improve the MIoU of crack edge detection and the accuracy of maximum crack width measurement under the non‐ideal shooting conditions of the actual inspection situation by automatically approaching the vicinity of the crack. [ABSTRACT FROM AUTHOR]

Understanding the uncontrolled passive dynamics of flying insects is important for evaluating the constraints under which the insect flight control system operates and for developing biomimetic robots. Passive dynamics is typically analyzed using computational fluid dynamics (CFD) methods, relying on the separation of the linearized hovering dynamics into longitudinal and lateral parts. While the longitudinal dynamics are relatively understood across several insect models, our current understanding of the lateral dynamics is lacking, with a nontrivial dependence on wing–wing interaction and on the details of wing kinematics. Particularly, the passive stability of the fruit fly, D. melanogaster, which is a central model in insect flight research, has so far been analyzed using simplified quasi-steady aerodynamics and synthetic wing kinematics. Here, we perform a CFD-based lateral stability analysis of a hovering fruit fly, using accurately measured wing kinematics, and considering wing–wing interaction. Lateral dynamics are unstable due to an oscillating–diverging mode with a doubling time of 17 wingbeats. These dynamics are determined by wing–wing interaction and the wing elevation kinematics. Finally, we show that the fly's roll controller, with its one wingbeat latency, is consistent with the lateral instability. This work highlights the importance of accurate wing kinematics and wing–wing interactions in stability analyses and forms a link between such passive instability and the insects' controller. [ABSTRACT FROM AUTHOR]

In this study, a novel framework for the flight control of a morphing unmanned aerial vehicle (UAV) based on linear parameter-varying (LPV) methods is proposed. A high-fidelity nonlinear model and LPV model of an asymmetric variable-span morphing UAV were obtained using the NASA generic transport model. The left and right wing span variation ratios were decomposed into symmetric and asymmetric morphing parameters, which were then used as the scheduling parameter and the control input, respectively. LPV-based control augmentation systems were designed to track the normal acceleration, angle of sideslip, and roll rate commands. The span morphing strategy was investigated considering the effects of morphing on various factors to aid the intended maneuver. Autopilots were designed using LPV methods to track commands for airspeed, altitude, angle of sideslip, and roll angle. A nonlinear guidance law was coupled with the autopilots for three-dimensional trajectory tracking. A numerical simulation was performed to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Innovative design intricacies of new generation of UAVs, necessitate formulation of control laws utilizing intelligent techniques which are independent of underlying dynamic model besides being robust to changing environment. In current research, a novel control architecture is presented for maximizing glide range of the UAV which bears an unconventional design. To handle the control complexities emerging due to the unique design of the UAV, a distinct RL technique named 'optimal dynamic programming' is proposed which besides being computationally acceptable also effectively controls the entire flight regime of the UAV. The proposed methodology has been specifically modified to configure the problem in continuous state and control space domains. The efficacy of the results and performance characteristics, demonstrated the ability of the presented algorithm to dynamically adapt to the changing environment, thereby making it suitable for UAV applications. Nonlinear simulations performed under different environmental conditions demonstrated the effectiveness of the proposed methodology over the conventional classical approaches. [ABSTRACT FROM AUTHOR]

In this paper, the design problem of Gain‐Scheduled Output‐Feedback (GSOF) controllers using inexact scheduling parameters for morphing aircraft during the wing transition process is addressed. Both the stability of the closed‐loop system and the L2 gain performance can be guaranteed under the controller based on measured (not actual) scheduling parameters. Firstly, the linear parameter‐varying (LPV) model of morphing aircraft is established by Jacobian linearization and the additive uncertainty is introduced into the scheduling parameters. By employing non‐linear transformations, the problem is formulated as the solution to a set of parameter‐dependent linear matrix inequalities (LMI) with a single‐line search parameter. Finally, the robustness of the flight control system to the wing transition process is verified under the condition of both the uncertainty of aerodynamic parameters and of scheduling parameters. [ABSTRACT FROM AUTHOR]

An adaptive controller and a nonlinear rate limiter are presented in order to improve the flight safety of manually controlled reentry vehicles and supersonic transport (SST) aircraft. The adaptive controller is based on the principle of dynamic inversion. The calculation of the controller parameters corresponding to the aerodynamic coefficients of the vehicle was carried out by a proposed online identification procedure. The effectiveness of the adaptive controller was tested through a set of experiments performed using a ground-based simulator. The obtained results were used to estimate the probability of an accident due to pilot error for the basic Space Shuttle flight control system and for its improved version with the adaptive controller. It was found that using the adaptive controller causes high required rates of elevon deflection. Because of the actuator's rate limiting, this is a source of pilot-induced oscillations. To counteract these oscillations in the pilot-vehicle closed loop system, an adaptive nonlinear rate limiter is introduced. The effectiveness of using the adaptive prefilter for improving the flight safety and flying qualities of the Space Shuttle reentry vehicle and an SST was demonstrated in experiments involving a ground-based simulator. • Real time dynamics identification ensures fast adaptive control. • Flight safety is considerably improved using adaptive flight control. • A well designed adaptive prefilter eliminates PIOs arising in case of low actuator rate limiting. • Adaptive flight control systems provide a considerable improvement of pilot-vehicle system performance. [ABSTRACT FROM AUTHOR]

The number of operations incorporating E-VTOL aircrafts is increasing each year, and the optimization of the energy consumption of such vehicles is a major problem. In this paper, a small-scale ARCHER helicopter's energy consumption is analyzed, wherein different flight conditions, main rotor revolutions, and flight control system settings are considered. The helicopter dynamic model was developed in the FLIGHTLAB environment and was then validated based on flight test data. The model used for the calculation of energy consumption was developed using the electric and dynamic characteristics of the main rotor, electric motor, and transmission system. The main part of this work concerns the analysis of electric energy consumption during the vehicle's flight via the use of an automatic flight control system (AFCS) that ensures repeatable flight conditions. The AFCS was designed such that it includes both path and attitude control to provide hover and cruise control modes. The helicopter's energy consumption was analyzed during different phases of flight, when executing maneuvers, and using different main rotor angular velocities to perform - a given task. The results show that the level of energy consumption significantly depends on the helicopter's main rotor revolutions, flight speed, and the maneuvers performed. The proposed methodology can be used in prospective energy-efficient mission planning and UAV helicopter design. [ABSTRACT FROM AUTHOR]

The hardware and software of the flight control system of tandem unmanned helicopter were designed using embedded design technology. For the hardware of the flight control system, STM32 H750 VBT6 was used as the main control chip of the system, and the multi-sensor attitude measurement hardware system was constructed using 6-axis motion processing sensor LSM6 DSR and three-axis magnetometer LIS2 MDL. The timer on the main control chip was used to receive remote control input signal, output PWM motor control signal and steering gear control signal. For the flight control system software, the quaternion complementary filtering method was used to fuse the acceleration and angular velocity measured by the inertial navigation module and the three-axis magnetic field intensity measured by the magnetometer, and the flight attitude of the UAV was calculated. Cascade control strategy was adopted in the control strategy. The attitude angle of the UAV was controlled by the outer loop controls, and the attitude angular velocity of the UAV was controlled by the inner loop controls to achieve rapid and accurate control of the UAV attitude. The results show that the software and hardware of the flight control system of tandem unmanned helicopter are realized, and the expected results are achieved according to the flight test verification. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to offer a simultaneous design approach for helicopter having swept anhedral blade tip shape and helicopter flight control system (HFCS) to minimize controller cost. Design/methodology/approach: By considering previously stated offer, control-oriented models and a stochastic optimization method are applied to minimize controller cost of the HFCS. Findings: Using simultaneous design approach for helicopters having blade tip swept and blade tip anhedral causes considerably less control effort than the helicopters not benefiting this related design approach. Practical implications: Simultaneous design approach for helicopters having blade tip swept and blade tip anhedral is applicable to consider fuel economy. Originality/value: One important novelty of this paper is using simultaneous approach for determining optimum shape of blade tip swept and anhedral. Another considerable novelty of this paper is also using a stochastic optimization method called simultaneous perturbation stochastic approximation for previously mentioned purpose. In this paper, it is also reached that using simultaneous design approach for swept anhedral helicopter blade tip shape and HFCS causes less control effort than the helicopters not using this approach. This leads to less fuel consumption and green environment. [ABSTRACT FROM AUTHOR]