Quadrotor Unmanned Aerial Vehicle Research Articles

A Comparative Study for Control of Quadrotor UAVs

Modeling and controlling highly nonlinear, multivariable, unstable, coupled and underactuated systems are challenging problems to which a unique solution does not exist. Modeling and control of Unmanned Aerial Vehicles (UAVs) with four rotors fall into that category of problems. In this paper, a nonlinear quadrotor UAV dynamical model is developed with the Newton–Euler method, and a control architecture is proposed for 3D trajectory tracking. The controller design is decoupled into two parts: an inner loop for attitude stabilization and an outer loop for trajectory tracking. A few attitude stabilization methods are discussed, implemented and compared, considering the following control approaches: Proportional–Integral–Derivative (PID), Linear–Quadratic Regulator (LQR), Model Predictive Control (MPC), Feedback Linearization (FL) and Sliding Mode Control (SMC). This paper is intended to serve as a guideline work for selecting quadcopters’ control strategies, both in terms of quantitative and qualitative considerations. PID and LQR controllers are designed, exploiting the model linearized about the hovering condition, while MPC, FL and SMC directly exploit the nonlinear model, with minor simplifications. The fast dynamics ensured by the SMC-based controller together with its robustness and the limited estimated command effort of the controller make it the most promising controller for quadrotor attitude stabilization. The outer loop consists of three independent PID controllers: one for altitude control and the other two, together with a dynamics’ inversion, are entitled to the computation of the reference attitude for the inner loop. The capability of the controlled closed-loop system of executing complex trajectories is demonstrated by means of simulations in MATLAB/Simulink®.

Task-independent auditory probes reveal changes in mental workload during simulated quadrotor UAV training.

The event-related potential (ERP) methods based on laboratory control scenes have been widely used to measure the level of mental workload during operational tasks. In this study, both task difficulty and test time were considered. Auditory probes (ignored task-irrelevant background sounds) were used to explore the changes in mental workload of unmanned aerial vehicle (UAV) operators during task execution and their ERP representations. 51 students participated in a 10-day training and test of simulated quadrotor UAV. During the experiment, background sound was played to induce ERP according to the requirements of oddball paradigm, and the relationship between mental workload and the amplitudes of N200 and P300 in ERP was explored. Our study shows that the mental workload during operational task training is multi-dimensional, and its changes are affected by bottom-up perception and top-down cognition. The N200 component of the ERP evoked by the auditory probe corresponds to the bottom-up perceptual part; while the P300 component corresponds to the top-down cognitive part, which is positively correlated with the improvement of skill level. This paper describes the relationship between ERP induced by auditory probes and mental workload from the perspective of multi-resource theory and human information processing. This suggests that the auditory probe can be used to reveal the mental workload during the training of operational tasks, which not only provides a possible reference for measuring the mental workload, but also provides a possibility for identifying the development of the operator's skill level and evaluating the training effect.

Adaptive fractional‐order nonsingular fast terminal sliding mode formation control of multiple quadrotor UAVs‐based distributed estimator

AbstractThis paper mainly solves two major problems that are unavoidable in leader–follower formation process of quadrotor UAV group: the existence of external uncertainty disturbance and communication limited between quadrotor unmanned aerial vehicle (UAV) group. To solve the problem that only one of the followers in the leader–follower formation can obtain the leader's information, an improved distributed estimator is proposed in this paper, which can accurately estimate the leader's information for each follower. In addition, in order to eliminate the influence of uncertain external disturbance on the performance of quadrotor UAV, an adaptive estimation law is designed based only on velocity and position variables. For the attitude and position subsystem of the quadrotor UAV, a sliding surface with fractional‐order term is designed. Which makes the quadrotor UAV tracking error system obtain good robustness at the stage of reaching the sliding surface and fast convergence and accurate tracking performance in the sliding stage. Based on Lyapunov stability theory, the convergence results are analyzed strictly. The results show that the algorithm can make the position distance between leader and followers converge to the desired offset. Simulation results verify the effectiveness and superiority of the control algorithm.

Attitude Control of the Quadrotor UAV with Mismatched Disturbances Based on the Fractional-Order Sliding Mode and Backstepping Control Subject to Actuator Faults

Considering mismatched disturbances, aerodynamic interference, chattering, and actuator failure in the attitude control of the quadrotor unmanned aerial vehicle (UAV), this paper establishes a new quadrotor UAV model with mismatched disturbances, based on quaternion, and designs a fault tolerant controller. First, in order to reduce the chattering of the traditional reaching law, a new reaching law based on the sigmoid function is introduced into the design. Second, the sliding mode control and backstepping control methods are adopted, based on the new fractional-order sliding mode surface when the faults occur in quadrotor UAV actuators, and parameters in the sliding mode control are adaptively adjusted. The simulation results show that the fault tolerant control method can control the attitude of UAV quickly and achieve good robustness.

Safety Flight Control Design of a Quadrotor UAV With Capability Analysis

This article considers the safety control problem of a quadrotor unmanned aerial vehicle (UAV) subject to actuator faults and external disturbances, based on the quantization of system capability and safety margin. First, a trajectory function is constructed online with backpropagation of system dynamics. Therefore, a degraded trajectory is gracefully regenerated, via the tradeoff between the remaining system capability and the expected derivatives (velocity, jerk, and snap) of the trajectory. Second, a control-oriented model is established into a form of strict feedback, integrating actuator malfunctions and disturbances. Therefore, a retrofit dynamic surface control (DSC) scheme based on the control-oriented model is developed to improve the tracking performance. When comparing to the existing control methods, the compensation ability is analyzed to determine whether the faults and disturbances can be handled or not. Finally, simulation and experimental studies are conducted to highlight the efficiency of the proposed safety control scheme.

Terminal sliding mode attitude-position quaternion based control of quadrotor unmanned aerial vehicle

In this paper is presented the development of a terminal sliding mode attitude-position quaternion based control of a quadrotor unmanned aerial vehicle UAV. First, the dynamics of this UAV is divided into an attitude and position loop in order to design suitable independent control laws. The type of control law implemented for each loop is of the kind of hybrid terminal sliding mode and quaternion controller. The advantages of these control strategies over other techniques found in the literature are that the implementation of a quaternion based control strategy provides a relatively simple approach considering that the dynamics for the attitude and position loops can be described in this way. The quaternion based control strategy is suitable considering the kinematic and dynamic model of a quadrotor UAV, meanwhile the sliding mode controller part provides a relativelly simple control strategy taking into consideration that is reliable against uncertainties and provide a fast and accurate attitude-position tracking considering a reference to be followed by each loop. It is important to take into consideration that when an attitude command is given, the closed loop dynamics of the attitude block is stabilized generating at the same time the reference for the position loop. The terminal sliding mode controller part is obtained by selecting an appropriate sliding surface in order that the control law for each loop would be drove to the reaching phase faster and accurately. It is worthy to mention that both control loops posses feedforward neural networks as compensators in order that the tracking error will be reduced by both control strategies. Finally, a numerical experiment is conducted in order that the theoretical results are validated offering the appropriate discussion and conclusions about this research study.

Real-time nonlinear parameter estimation and tracking control of unmanned aerial vehicles in closed-loop

The real-time unknown parameter estimation and adaptive tracking control problems are investigated in this paper for a six degrees of freedom (6-DOF) of under-actuated quadrotor unmanned aerial vehicle (UAV). A virtual proportional derivative (PD) controller is designed to maintain the translational dynamics. Two adaptive schemes are developed to handle the attitude dynamics of the UAV with several unknown parameters. In the beginning, a classical adaptive scheme (CAS) using the certainty equivalence principle is proposed and designed. The idea is to design a controller for an ideal situation by assuming the unknown parameters were known. Then the unknown parameters are replaced by their estimation. A theoretical analysis is provided to ensure the trajectory tracking of the adaptive controller. However, an inherent drawback of this scheme is that there is no guarantee for the estimated parameters to converge to the actual values. To address this issue, a new adaptive scheme (NAS) is developed as the next step by adding a continuously differentiable function to the control structure. The proposed technique guarantees handling of the parametric uncertainties with an appropriate design manifold. A rigorous analytical proof, numerical simulation analyses, and experimental validation are presented to show the effectiveness of the proposed control design.

A Switching Mode Control Scheme for the Hovering Control of Quadrotor Unmanned Aerial Vehicles

This paper presents a novel switching mode control scheme for the six-DOF hovering control of underactuated quadrotor unmanned aerial vehicles (QUAVs) with strong coupling. Through this paper, the full six states of the position and attitude of the QUAV can be controlled to the special target configuration in a fixed time. First, a continuously differentiable fixed time controller with a state constraint was designed for the position system. Second, a fixed-time integral sliding mode controller was designed for the attitude subsystem. Thirdly, a switching law was designed to switch the above two types of controllers a limited number of times during hovering control. Additionally, the crash problem is fully discussed during the entire control process. In summary, the full-state hover mission was completed. The simulation experiments verify the effectiveness of the control algorithm.

An adaptive sliding mode fault‐tolerant control of a quadrotor unmanned aerial vehicle with actuator faults and model uncertainties

AbstractAn adaptive sliding mode fault‐tolerant control strategy is proposed for a quadrotor unmanned aerial vehicle in this article to accommodate actuator faults and model uncertainties. First, a new reaching law is proposed, with which a sliding mode control (SMC) law is constructed. The proposed reaching law is made up of a sliding variable and the distance between it and a designated boundary layer, and it can effectively suppress the unexpected control chattering while preserving the necessary system tracking performance. Then, an adaptive SMC scheme is proposed to further solve the fault and uncertainty compensation problem. The proposed adaptation law helps to prevent overestimation of the adaptive control parameters, as well as avoiding control chattering. Finally, a number of comparative simulation tests are carried out to validate the effectiveness and superiority of the proposed control strategy. The demonstrated quantitative comparison results confirm its advantages.

Adaptive Fault-Tolerant Tracking Control of Quadrotor UAVs against Uncertainties of Inertial Matrices and State Constraints

This paper presents a study on a quadrotor unmanned aerial vehicle (UAV) fault-tolerant control scheme. According to the attitude model and safety control of the aircraft under the uncertainty of inertial matrix, the attitude state constraint by reinforcement learning is designed to ensure safety. Even if the boundary is crossed, it can be pulled back to the boundary by means of a designed penalty function with reinforcement learning. Meanwhile, in order to inhibit the oscillation caused by immediate reward as usual, an adaptive update law is proposed. Furthermore, considering the coupled actuator fault and system input saturation due to uncertainty of inertial matrix, the Nussbaum-type function is utilized in this work to handle this challenge, which likely causes the singularity of inertia matrix. As a consequence, combined with the Lyapunov stability theory, it is confirmed that the proposed FTC scheme ensures that all the closed-loop signals are bounded. Simulation results are carried out to illustrate the effectiveness and advantage of the proposed control scheme.

Unmanned Aerial Transportation System With Flexible Connection Between the Quadrotor and the Payload: Modeling, Controller Design, and Experimental Validation

Aerial delivery is becoming a reality due to the development of microelectronics and communication technology. Most existing methods for cable-suspended transportation systems utilize fixed-length cable to connect the unmanned aerial vehicle quadrotor and the payload. Such aerial transportation systems present underactuated property, which is caused by the indirectly controllable payload motion and the underactuation of the quadrotor itself. In practical applications, payload hoisting and lowering motion independent of the quadrotor altitude will further expand the application scope in such areas as limited space crossing and offshore sample collection. To realize the aforementioned objectives, a flexible connection between the quadrotor and the payload is realized by mounting an actuator beneath the fuselage. Suffering from strong nonlinearity and complex dynamic coupling, the control problem becomes extremely challenging and more cumbersome, as the system’s degree of freedom (DOF) increases. To deal with these problems, in this article, a nonlinear control approach is presented by energy-based analysis, which achieves simultaneous quadrotor positioning, payload swing elimination and hoisting <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">/</b> lowering. Lyapunov techniques and LaSalle’s Invariance theorem are utilized to prove the asymptotic convergence of the equilibrium point. Finally, a series of hardware experiments are conducted on a self-built aerial transportation platform. As far as we know, this article provides the first mechanism and control solution for payload hoisting/lowering independent of the quadrotor altitude.

Obstacle Avoidance Control of Unmanned Aerial Vehicle with Motor Loss-of-Effectiveness Fault Based on Improved Artificial Potential Field

This paper presents an obstacle avoidance control strategy for an underactuated quadrotor unmanned aerial vehicle with motor loss-of-effectiveness fault and disturbance. The control system is divided into two parts: the obstacle avoidance loop and the tracking loop. By introducing the height factor in the artificial potential field function, an improved obstacle avoidance strategy is designed in the obstacle avoidance loop. Compared with the existing literature, the proposed obstacle avoidance strategy can avoid falling into the trap of the local optimum when a UAV encounters obstacles. At the same time, considering the sudden motor loss-of-effectiveness fault of UAV, adaptive technology is used to estimate the fault parameters online to restrain the effects of motor loss-of-effectiveness fault in the tracking loop. The stability of the closed-loop UAV system is guaranteed by stabilizing each of the subsystems through backstepping technology. Simulations are conducted to demonstrate the effectiveness of the designed obstacle avoidance control strategy.

Adaptive Nonsingular Fast Terminal Sliding Mode Control of Aerial Manipulation Based on Nonlinear Disturbance Observer

Aimed at resolving the trajectory tracking control problem of aerial manipulation, this paper presents an aerial manipulation system that consists of a quadrotor unmanned aerial vehicle (UAV) and a two-degree-of-freedom manipulator. The system adopted an integrated control strategy; that is, the rotor UAV and the manipulator were considered as a whole, the coupling effect was treated as an internal factor, and the whole was taken as the research object to establish a dynamic model. Then, by combining the nonsingular fast terminal sliding mode controller with the adaptive controller, an adaptive nonsingular fast terminal sliding mode controller was designed. A composite control rate based on the nonlinear disturbance observer and the adaptive nonsingular fast terminal sliding mode was determined in order to compensate for the external disturbance and the internal modeling error of the system as well as to ensure its rapid convergence. Finally, the different control methods were simulated by setting the operational tasks. The simulation results show that the proposed control method is effective.

Visual servoing of quadrotor UAVs for slant targets with autonomous object search

In this paper, an enhanced visual servoing method is designed for a quadrotor unmanned aerial vehicle (UAV) based on virtual plane image moments, under underactuation and tight coupling constraints of UAV kinematics. Moreover, in order to make the UAV search visual targets autonomously in target vicinity during flight, a flexible flight system is developed with stages of take-off, target searching, and image-based visual servoing (IBVS). With dual-camera sensor configuration, the UAV system searches targets from given directions while making localization. A virtual image plane is constructed and image moments are adopted to decouple UAV lateral movement. For a non-horizonal target, homography is utilized to construct the target plane and transform it into a horizonal plane. Backstepping techniques are used to derive the nonlinear controller to realize the IBVS strategy. Stability analysis proves global asymptotic performance of the closed-loop system. Experimental verification shows feasibility of the overall flight system and effectiveness of the visual servoing controller.

Fault-tolerant control of second-order systems based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode

In this article, a fault-tolerant control method based on augmented improved extended state observer and non-singular high-order fast terminal sliding mode is proposed for a class of second-order systems with actuator faults. First, the initial peak of the traditional extended state observer is avoided by improving the structure of the observer. Second, the total disturbance and its change trend are observed simultaneously, so as to better realize the compensation of total disturbance. The convergence of the observer is proved theoretically. In addition, by designing non-singular high-order fast terminal sliding mode surface, the sliding mode variable converges rapidly during the whole process to improve the algorithm’s rapidity. Finally, the chattering of control signal caused by sliding mode control is greatly reduced using high-order sliding mode technology, and the stability of the whole closed-loop system is proved by Lyapunov criterion. The comparative experimental results on the fault-tolerant control platform of the quadrotor unmanned aerial vehicle demonstrate the effectiveness and superiority of the proposed observer and controller.

Missing data reconstruction in attitude for quadrotor unmanned aerial vehicle based on deep regression model with different sensor failures

Forming a UAV cluster with multiple UAVs to collaborate in accomplishing tasks is the future development of battlefield. The UAV cluster can collaborate by communicating through inter-aircraft links and can quickly and accurately perform complex tasks such as path planning, collaborative reconnaissance, collaborative sensing and attack. In the process of Unmanned Aerial Vehicle (UAV) cooperative operation, obtaining the real-time attitude information of each UAV is preliminary to implement collaborative cooperation. However, in practice, due to the internal malfunction of sensors and mutual interference among UAVs, the acquired attitudes often suffer from data missing. This paper proposed a novel missing data reconstruction method for UAV’s attitude in the case of sensor failures. The attitude data of UAV is obtained through an advanced UAV simulation platform AirSim. Through fusing the temporal convolutional network (TCN) and Bi-directional long short-term memory (Bi-LSTM), a deep regression framework is established for missing data construction. In addition, we evaluate the reliability of the proposed method by comparing with different baseline models and different combinations of data missing. The performance of our method is quantified using metrics of root-mean-square-error (RMSE), mean absolute error (MAE), determination coefficient (DC), mean absolute percentage error (MAPE), and symmetric mean absolute percentage error (SMAPE) score. The averaged performance values of our proposed method outperform other baseline algorithms. The results of the experiment show that the study could well-address the issue of missing data reconstruction and provide reliable attitude data.

Deep-Reinforcement-Learning-Based Multitarget Coverage With Connectivity Guaranteed

Deriving a distributed, time-efficient, and connectivity-guaranteed coverage policy in multitarget environment poses huge challenges for a multirobot team with limited coverage and limited communication. In particular, the robot team needs to cover multiple targets while preserving connectivity. In this article, a novel deep-reinforcement-learning-based approach is proposed to take both multitarget coverage and connectivity preservation into account simultaneously, which consists of four parts: a hierarchical observation attention representation, an interaction attention representation, a two-stage policy learning, and a connectivity-guaranteed policy filtering. The hierarchical observation attention representation is designed for each robot to extract the latent features of the relations from its neighboring robots and the targets. To promote the cooperation behavior among the robots, the interaction attention representation is designed for each robot to aggregate information from its neighboring robots. Moreover, to speed up the training process and improve the performance of the learned policy, the two-stage policy learning is presented using two reward functions based on algebraic connectivity and coverage rate. Furthermore, the learned policy is filtered to strictly guarantee the connectivity based on a model of connectivity maintenance. Finally, the effectiveness of the proposed method is validated by numerous simulations. Besides, our method is further deployed to an experimental platform based on quadrotor unmanned aerial vehicles and omnidirectional vehicles. The experiments illustrate the practicability of the proposed method.

Sveobuhvatan pregled različitih strategija upravljanja za bespilotne letelice kuadrotor

The Quadrotor Unmanned Aerial Vehicles (UAVs) have gained significant attention in recent years due to their versatile applications in civilian and military sectors. It is a highly nonlinear and underactuated system and an outdoor flight; it is always subjected to external disturbances due to wind gusts and other environmental factors. Implementing the control strategies could be improved in terms of high computational time, uncertainty, approximation error, and a large amount of training data. One of the major challenges in the development of quadrotors is the design of an efficient and reliable control system. This paper presents a comprehensive review of various control strategies for quadrotors and evaluates their performance. The review includes classical control techniques such as PID (Proportional-Integral-Derivative) and LQR (Linear Quadratic Regulator) and modern control strategies such as adaptive and fuzzy control. Comparative analysis of various control strategies has been presented with key challenges and future directions. This study provides a useful guide for researchers and engineers in the design of control systems for quadrotors.

Adaptive backstepping position tracking control of quadrotor unmanned aerial vehicle system

&lt;abstract&gt;&lt;p&gt;In this work, an adaptive backstepping position tracking control using neural network (NN) approximation mechanism is proposed with respect to the translational system of quadrotor unmanned aerial vehicle (QUAV). Concerning the translational system of QUAV, on the one hand, it does not satisfy the matching condition and is an under-actuation dynamic system; on the other hand, it is with strong nonlinearity containing some uncertainty. To achieve the control objective, an intermediary control is introduced to handle the under-actuation problem, then the backstepping technique is combined with NN approximation strategy, which is employed to compensate the uncertainty of the system. Compared with traditional adaptive methods, the proposed adaptive NN position control of QUAV can alleviate the computation burden effectively, because it only trains a scalar adaptive parameter instead of the adaptive parameter vector or matrix. Finally, according to Lyapunov stability proof and computer simulation, it is proved that the control tasks can be accomplished.&lt;/p&gt;&lt;/abstract&gt;

SPT-Based Composite Hierarchical Antidisturbance Control Applied to a Quadrotor UAV

Although the flight control of quadrotor unmanned aerial vehicles have been widely studied, it is still very challenging to suppress multiple disturbances and efficiently utilize the inherent multi time-scale characteristics. As a well-known antidisturbance strategy, composite hierarchical antidisturbance control (CHADC) can compensate and attenuate disturbances simultaneously, thus enhancing the control performance of complex systems significantly. In the meantime, the singular perturbation theory (SPT) is employed to analyze the multi time-scale properties, and the original system is decomposed into the slow and fast subsystems. In this article, we present an antidisturbance control scheme based on the SPT and CHADC to enhance the capability of antidisturbance. A novel composite hierarchical antidisturbance (CHAD) predictor–corrector is proposed for the slow subsystem to integratively handle the disturbances from guidance and control perspective, and a CHAD <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{H}_{\infty }}$</tex-math></inline-formula> controller is employed for the fast subsystem subject to external disturbances and inertial uncertainties. Meanwhile, the compensability of disturbance is explicitly analyzed. Finally, experiments are carried out to validate the effectiveness of the proposed scheme.