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This paper presents a novel approach utilizing a sliding mode controller to control a quadrotor effectively in the presence of structural faults. While previous research has extensively explored fault-tolerant control for UAVs, particularly addressing faulty actuators and sensors, there remains a significant gap in addressing control methods for quadrotors experiencing structural faults. We focus specifically on scenarios where a fault in one of the quadrotor's rotors diverts thrust from the vertical axis, complicating traditional control methods. Our proposed method involves two key steps: firstly, identifying the fault vector using a terminal sliding mode observer, and secondly, calculating appropriate control inputs using a sliding mode method based on the estimated fault vector. Simulation results demonstrate the robustness of this approach, showing accurate control performance even in the presence of multiple faults and disturbances. The system's reliability hinges on the convergence of the disturbance observer's estimation error to zero within a finite time frame. In conclusion, the developed controller offers a dependable solution for safely controlling a faulty quadrotor amidst high nonlinearity and uncertainty. [ABSTRACT FROM AUTHOR]

Summary: The paper is devoted to the prescribed finite time attitude control for quadrotors. A novel prescribed finite time function is introduced, which is independent of initial conditions and design parameters. And a switched prescribed finite time controller is firstly designed, such that the quadrotor can not only converge to the desired attitude in a prescribed time, but also guarantee the stability of the quadrotor after the settling time. Simultaneously, it effectively avoids chattering issues at the controller's switching points. Finally, the simulation comparisons are carried out between the proposed control strategy and infinite time, finite time, traditional prescribed finite time control schemes to demonstrate the superiority of the developed controller. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV)-type Quadrotors are highly nonlinear systems that are difficult to control and stabilize outdoors, especially in a windy environment. Many algorithms have been proposed to solve the problem of trajectory tracking using UAVs. However, current control systems face significant hurdles, such as parameter uncertainties, modeling errors, and challenges in windy environments. Sensitivity to parameter variations may lead to performance degradation or instability. Modeling errors arise from simplifications, causing disparities between assumed and actual behavior. Classical controls may lack adaptability to dynamic changes, necessitating adaptive strategies. Limited robustness in handling uncertainties can result in suboptimal performance. Windy environments introduce disturbances, impacting system dynamics and precision. The complexity of wind modeling demands advanced estimation and compensation strategies. Tuning challenges may necessitate frequent adjustments, posing practical limitations. Researchers have explored advanced control paradigms, including robust, adaptive, and predictive control, aiming to enhance system performance amidst uncertainties in a scientifically rigorous manner. Our approach does not require knowledge of UAVs and noise models. Furthermore, the use of the Type-2 controller makes our approach robust in the face of uncertainties. The effectiveness of the proposed approach is clear from the obtained results. In this paper, robust and optimal controllers are proposed, validated, and compared on a quadrotor navigating an outdoor environment. First, a Type-2 Fuzzy Logic Controller (FLC) combined with a PID is compared to a Type-1 FLC and Backstepping controller. Second, a Genetic Algorithm (GA) is proposed to provide the optimal PID-Type-2 FLC tuning. The Backstepping, PID-Type-1 FLC, and PID-Type-2 FLC with GA optimization are validated and evaluated with real scenarios in a windy environment. Deep robustness analysis, including error modeling, parameter uncertainties, and actuator faults, is considered. The obtained results clearly show the robustness of the optimal PID-Type-2 FLC compared to the Backstepping and PID-Type-1 FLC controllers. These results are confirmed by the numerical index of each controller compared to the PID-type-2 FLC, with 12% for the Backstepping controller and 51% for the PID-Type-1 FLC. [ABSTRACT FROM AUTHOR]

Quadrotors are expected to play an active role in out-of-sight areas such as equipment inspection and transportation of supplies to disaster areas. However, ensuring stable and highly accurate automatic flights has become a significant challenge. Trajectory tracking control methods that combine adaptive output feedback control based on almost strictly positive real characteristics and backstepping strategy have been proposed for a quadrotor control system with nonlinearities. These methods have simple structures and are robust. However, existing adaptive control methods have the problem of singularities, owing to the use of Euler angles in the modeling of quadrotors. In this paper, we propose an adaptive control method that enables a wider range of attitude changes using quaternions. The effectiveness of the proposed method is validated through numerical simulations. [ABSTRACT FROM AUTHOR]

In this study, we developed a docking mechanism for drones that enables docking and undocking in the air for cargo transportation. This capability allows the drone configuration to be adapted depending on the cargo size and shape. We introduced a novel docking mechanism that incorporates magnetic adsorption and a newly engineered locking mechanism. We developed a drone detection system capable of estimating the relative position of a target drone by utilizing an onboard camera to identify the infrared LEDs on the target drone via image processing. Moreover, flight experiments, including detection, docking, and undocking, were performed using a mock drone to demonstrate the effectiveness of the developed system. [ABSTRACT FROM AUTHOR]

This paper proposes a novel controller design using adaptation based modified super twisting control to facilitate trajectory tracking and hovering maneuvers for the quadrotor. The controller gains of the existing modified super twisting control require bounds on the disturbance for trajectory tracking and hovering of the quadrotor. In this paper, the controller gains are adapted using the proposed dynamic adaptation law without knowing the actual disturbance or their upper bounds. The controller is designed within a nonlinear framework without performing linearization of quadrotor dynamics, which enables the proposed controller to remain effective even when the states deviate significantly from their nominal values. The performance of trajectory tracking and hovering of the quadrotor in the presence of disturbance is demonstrated using numerical simulations. In order to assess the effectiveness of the controller, the performance of the adaptation based modified super twisting control is compared to the existing modified super twisting control, and the proposed controller outperforms the existing one. • Adaptive modified super twisting control for robust trajectory tracking and hovering. • Dynamic adaptation law relaxes the need for an upper bound on disturbance. • Numerical simulations show the validity of the proposed approach. • Performance is compared with the existing modified super twisting control. • Efficacy is demonstrated with Dryden wind and sinusoidal disturbances. [ABSTRACT FROM AUTHOR]

The current paper discusses the application of Sliding Mode Control (SMC) to a quadcopter. The controller is designed based on the system's nonlinear model. An adaptive sliding mode controller is developed specifically for the quadcopter's attitude subsystem, aiming to mitigate the undesirable vibration phenomena typically associated with conventional sliding mode controllers while ensuring robust trajectory tracking for the quadcopter's attitude. The stability of the proposed controller was verified using the Lyapunov stability theorem. The quadcopter Unmanned Aerial Vehicle (UAV) model and the performance of the proposed controller were simulated and validated in MATLAB/SIMULINK environment. The results demonstrate that the proposed controller effectively positions the quadcopter with minimal error, maintaining the UAVs flight along the prescribed trajectory. Additionally, it performs well in trajectory tracking under collision noise and vibration reduction conditions. [ABSTRACT FROM AUTHOR]

Linear Quadratic Regulator (LQR) is one of the most prevalent methods used in the control of unmanned aerial vehicles. LQR controllers are commonly employed in the control of both linear and non-linear systems due to their advantages such as easy-to-apply and high-performance structure. However, there is one main difficulty that plays a significant role in the manner of determining the gain for the control signal: choosing appropriate weighting matrices. The selection of these matrices that directly affect the controller performance is generally performed by trial and error, which is laborious and time-consuming. Accordingly, various optimization algorithms have been utilized to determine the weighting matrices of the LQR controller. In this paper, the weighting matrices of the designed LQR controller were obtained using Standard Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, and Grey Wolf Optimization algorithms. The obtained weighting matrices of the LQR controller were tested on an unmanned aerial vehicle simulation, and the performance of optimization algorithms were presented comparatively. [ABSTRACT FROM AUTHOR]

This article tries to lower the load of computations and increase the robustness of a fault-tolerant control algorithm for quadrotors. In this method, neglecting the uncertainties, the quadrotor's dynamics is broken into two simple nonlinear models. A robust unscented Kalman filter is utilized for the fault estimation and reinforces a 2-Sliding Mode Controller. In this case, the unknown faults in multi-actuators are estimated. According to the Lyapunov theory, stability analysis is performed to discuss the reliability of the closed-loop FTC method. In the simulation results, comparing the performance of the proposed method with the performances of passive FTCs and augmented UKF estimators show the lighter computations and higher robustness of the presented algorithm for quadrotors resistant to unknown faults due to the testing scenarios. [ABSTRACT FROM AUTHOR]

Multicopters are used for a wide range of applications that often involve approaching buildings or navigating enclosed spaces. Opposed to the open spaces in obstacle-free environments commonly flown by fixed-wing unmanned aerial vehicles, multicopters frequently fly close to surfaces and must take into account the airflow variations caused by airflow rebound. Such disturbances must be identified in order to design algorithms capable of compensating them. The evaluation of ground, ceiling and wall effects using two different test stands is proposed in this work. Different propellers and sensors have been considered for testing. The first test setup used was placed inside terraXcube’s large climatic chamber allowing a precise control of temperature and pressure of around 20°C and 1000 hPa, respectively. The second test setup is located at the University of Denver (DU) Unmanned Systems Research Institute (DU 2 SRI) laboratory with a stable pressure of around 800 hPa. Two different fixed 6 degrees of freedom force-torque sensors have been used for the experiments, allowing to sample forces and moments in three orthogonal axes. The tests simulate a hovering situation of a quadcopter at different distances to either the ground, the ceiling or a wall. The influence of the propeller size, rotation speed, pressure and temperature have also been considered and used for later dimensionless coefficient comparison. A thorough analysis of the measurement uncertainty is also included based on experimental evaluations and manufacturer information. Experimental data collected in these tests can be used for the definition of a mathematical model in which the effect of the proximity to the different surfaces is evaluated. [ABSTRACT FROM AUTHOR]

In the last decade, quadrotors have gained popularity among industry and academia due to their capabilities and the various applications in which they can be found. In addition to the above, because this is an underactuated system, researchers have found it a great challenge to control. Despite this, there is a wide variety of methodologies in the literature to control this type of system. Based on the above, this work proposed an alternative to trajectory tracking control for quadrotor unmanned aerial vehicles (UAV). The problem was divided into two main control loops: an outer control loop for the position coordinates, tackled through linear active disturbance rejection controllers (ADRC), and an inner control loop related to the orientation variables, addressed via robust proportional-integral-differential (PID) controllers. Furthermore, a generalized proportional integral observer (GPIO) was implemented to estimate the velocity and internal and external disturbances; therefore, the control strategy only depended on the attitude (position and orientation) quadrotor measurements. Then, the control performance was tested through numerical simulations and experimental tests, including wind disturbance inputs. [ABSTRACT FROM AUTHOR]

This study reviews numerous control approaches utilized to address various issues encountered by unmanned aerial vehicles (UAVs). Specifically, focusing on the quadrotor system. Due to its versatility and compact size, quadrotors have gained popularity as UAVs in recent decades. Quadrotors face challenges such as ambient disturbances, impediments, non-parametric and parametric perturbations while performing tasks. Consequently, a robust and efficient control system is essential for such a system to ensure the stability and enhance their performance. It should be noted that, in this review, we have examined and analyzed the most recent highly cited papers selected from esteemed journals and magazines renowned for their exceptional quality and reputation.

Abstract In this paper, a dynamic quadrotor unmanned aircraft vehicle driven by bidirectional electronic speed controllers is proposed to enhance maneuverability and stability. Bidirectional electronic speed controllers are applied to achieve rapid deceleration of motors during flight. To match with bidirectional electronic speed controllers, fractional order Proportional-Integral-Derivative (PID) controllers are considered to attain better rapidity compared to PID controllers, and an innovative control allocation matrix with direction symbols is developed. The model, controllers, and allocation methods have been proven an effective scheme in simulations of attitude and position tracking.

In this paper, a dynamic quadrotor unmanned aircraft vehicle driven by bidirectional electronic speed controllers is proposed to enhance maneuverability and stability. Bidirectional electronic speed controllers are applied to achieve rapid deceleration of motors during flight. To match with bidirectional electronic speed controllers, fractional order Proportional-Integral-Derivative (PID) controllers are considered to attain better rapidity compared to PID controllers, and an innovative control allocation matrix with direction symbols is developed. The model, controllers, and allocation methods have been proven an effective scheme in simulations of attitude and position tracking. [ABSTRACT FROM AUTHOR]

In order to solve the problems of loss of moving targets due to the flight status of the unmanned aerial vehicle (UAV) itself, the interference of the environment the randomness of the target and other reasons in the process of collecting moving target image information by the UAV platform, a deep deterministic policy gradient (DDPG) algorithm UAV following method based on moving target recognition was proposed. Facing the vehicle target on the highway, the relationship among the height, posture and high-speed vehicle motion of the UAV was analyzed. the velocity adaptive model of the target detection frame rate of the mobile platform was estab lished, and the flight attitude and speed of the UAV were corrected in real time according to the motion state of the target, so that the UAV could maintain the relative position and angle with the target. Then, based on the value network of DDPG algorithm, the value of UAV taking spe- cific actions in different states was estimated; the strategy network generates the strategy of UAV taking actions in a given state, and gives UAV flight altitude and speed control parameters for target tracking, so that the UAV could automatically adjust the flight state according to the movement change of the target, and realize the adaptive tracking of the moving target. Simulation experiments show that the DDPG algorithm can provide stable flight attitude data and a reliable control basis for the UAV following task, and the UAV can track the ground moving target in a circular area with a speed range of 0~33 m/s and a radius of 120 m in real time, and can achieve continuous and stable tracking within the endurance range. [ABSTRACT FROM AUTHOR]

This paper is devoted to adaptive trajectory tracking of quadrotor systems with full-state constraints and random disturbances. The command-filtering technology combined with error compensation mechanisms is proposed to deal with the "explosion of complexity" problem in traditional backstepping design and reduction of the filtering errors. The Barrier Lyapunov functions (BLFs) are constructed to ensure that all system states do not violate the boundary of its constraints. The command-filtered adaptive fuzzy controller is designed such that the state constraints are not breached almost surely, all signals in the closed-loop system are bounded almost surely, and the first-order moment of the tracking error converges to an arbitrarily small neighborhood of zero by parameters tuning. Finally, the effectiveness of the proposed control method is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

The purpose of this article is to control the formation of heterogeneous flying robots and to cross obstacles. The robots in question are a quadrotor and two unmanned helicopters. Independent attitude and position of robots and formation flight are controlled by the sliding mode method. Improved Artificial Potential Fields has been used to avoid collision with dynamic and static obstacles. The results of the design of the attitude and position controller showed that the attitude and position of the robots were well stabilized and converged in less than 3 s, which is a favorable time. The results of the formation flight simulation were presented in the form of 4 missions. In the first mission, the quadrotor is considered the leader, and the helicopters are the followers. The flight formation is triangular and the flight path is spiral. The results showed that the followers follow the leader. In the second mission, the robot crosses dynamic and static obstacles and the leader tracks the fixed target. In the third mission, the number of followers increases to 5 and the flight formation is hexagonal. The obstacles in this mission are dynamic and the target is moving. The results showed that in these two missions, the leader tracks the target well and the robots maintain triangular and hexagonal flight formations after crossing the obstacles. The results of simulations of group crossing of obstacles showed that the simulation error is less than 4% according to the expected position of the robots, and show the efficiency of the applied methods. [ABSTRACT FROM AUTHOR]

In this paper, an on-line closed-loop identification of mainly mass and inertia of an under-actuated aerial vehicle, namely a quadrotor acting as an aerial manipulator, is presented. Being treated as a rigid body, only one set of eighteen- or six tri-axial linear accelerometers is used to facilitate such estimation. Force and torque disturbances acting upon the vehicle during identification are also estimated which will refine the overall estimation quality of the unknown parameters. Namely, recursive linear and nonlinear least squares methods are used to obtain initial and refined estimations, respectively. Random disturbances are introduced to the closed-loop system to ensure enough excitation of the overall system. Issues related to identifiability, stability and performance are discussed. Since the proposed method depends on general kinematical and dynamical analyses of motion, it is claimed that the presented method will be also applicable to a wider range of, mainly, aerial vehicles. [ABSTRACT FROM AUTHOR]

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Summary The formation category for multiple quadrotor drones with the distributed formation protocol is addressed. By exploiting an indoor optical motion capture location system, the formation flight experiment for practical multiple quadrotor drones is performed. Firstly, by decoupling the relationship of the outer and inner loop models, the control loop of a quadrotor drone is divided into the outer position and velocity loop and inner attitude loop, and the distributed formation protocol is constructed by outer‐loop states, where the neighboring relationship term and the formation registration term can regulate formation errors and the whole motion trajectory of multiple quadrotor drones, respectively. The self‐feedback mechanism of the quadrotor drone is introduced to regulate the motion trajectory of whole formation. Then, formation achievability criteria for multiple quadrotor drones are proposed, where two control gains are determined in an analytic form, and the whole motion trajectory for multiple quadrotor drones is presented. Finally, a formation achievement algorithm is proposed, where the formation protocol is implemented by the inner‐loop attitude control of each quadrotor drone, and a formation flight experiment is performed to show the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) and quadrotors are being used in an increasing number of applications. The detection and management of forest fires is continually improved by the incorporation of new economical technologies in order to prevent ecological degradation and disasters. Using an inner-outer loop design, this paper discusses an attitude and altitude controller for a quadrotor. As a highly nonlinear system, quadrotor dynamics can be simplified by assuming several assumptions. Quadrotor autopilot is developed using nonlinear feedback linearization technique, LQR, SMC, PD, and PID controllers. Often, these approaches are used to improve control and to reject disturbances. PDPID controllers are also deployed in the tracking and surveillance of smoke or fire by intelligent algorithms. In this paper, the efficiency using a combined PDPID controllers with adjustable parameters have been studied. The performance was assessed by simulation using matlab Simulink. The computational study conducted to assess the proposed approach showed that the PD-PID combination presented in this paper yields promising outcomes. [ABSTRACT FROM AUTHOR]

Quadrotors are widely applied in many fields, but they often face various external disturbances in actual operation. This makes it necessary to design a controller that can handle disturbances. Disturbance observer and adaptive control techniques are commonly used disturbance rejection techniques, the core idea of which is to estimate the disturbances in real time and incorporate the estimated values into the controller to suppress the disturbances. In this paper, various disturbance observers and adaptive control techniques, including nonlinear disturbance observers, extended state observers, neural networks, and fuzzy logic systems, are introduced, along with their variants or different structures. These techniques improve the adaptability and robustness of quadrotors to complex environments. Finally, future research directions for the disturbance rejection of quadrotors are also presented. [ABSTRACT FROM AUTHOR]

In this article, a novel control algorithm called the combined backstepping and feedback linearisation method, along with an uncertainty estimator, is presented for quadrotors. The objective is to develop a robust control algorithm capable of handling various flight conditions, compensating for uncertainties and disturbances, and effectively controlling high-speed manoeuvres. To accomplish this, the quadrotor dynamics model is first derived using the Newton–Euler method. Subsequently, a backstepping control algorithm is designed for the quadrotor's internal control layer, followed by the application of the feedback linearisation method to the external control layer. An estimator is also designed to mitigate the effects of disturbances and uncertainties. A comparison is made between the proposed combined backstepping and feedback linearisation algorithm and the backstepping method, revealing that the combined backstepping and feedback linearisation algorithm outperforms the backstepping method across different aspects. Notably, the combined backstepping and feedback linearisation algorithm achieves faster trajectory tracking and demonstrates fewer steady-state errors. Additionally, the integration of the uncertainty estimator into the combined backstepping and feedback linearisation algorithm effectively mitigates the detrimental effects of disturbances and uncertainties. Comparative results for tracking control are presented to evaluate the performance of the proposed algorithm across various scenarios and case studies. [ABSTRACT FROM AUTHOR]

An active disturbance suppression and model predictive control (MPC) strategy is proposed for the quadrotor precision trajectory tracking control problem under disturbance action and model uncertainty. The model predictive controller estimates and compensates the disturbance by the extended state observer (ESO) and disturbance observer (DO) to achieve the position loop accurate control. In the presence of external disturbances and parameter uncertainties, it is demonstrated through simulation experiments that the proposed method improves the robustness to modeling errors and disturbances, while achieving smooth tracking of the reference trajectory.