Control Of Unmanned Aerial Vehicles Research Articles

Constrained trajectory optimization and force control for UAVs with universal jamming grippers

This study presents a novel framework that integrates the universal jamming gripper (UG) with unmanned aerial vehicles (UAVs) to enable automated grasping with no human operator in the loop. Grounded in the principles of granular jamming, the UG exhibits remarkable adaptability and proficiency, navigating the complexities of soft aerial grasping with enhanced robustness and versatility. Central to this integration is a uniquely formulated constrained trajectory optimization using model predictive control, coupled with a robust force control strategy, increasing the level of automation and operational reliability in aerial grasping. This control structure, while simple, is a powerful tool for various applications, ranging from material handling to disaster response, and marks an advancement toward genuine autonomy in aerial manipulation tasks. The key contribution of this research is the combination of a UG with a suitable control strategy, that can be kept relatively straightforward thanks to the mechanical intelligence built into the UG. The algorithm is validated through numerical simulations and virtual experiments.

Distributed formation control of multi-UAV systems using relative information

An adaptive distributed control strategy is designed for the formation of multiple unmanned aerial vehicle (UAV) groups by using only relative measurement information. A distributed estimator is first designed to get the estimate of the consensus error. Then, an adaptive distributed controller is proposed to realize the formation tracking with the relative measurements. Based on the position and velocity information, a control barrier function (CBF) algorithm is applied to achieve the UAV formation under safe position constraints. In addition, in order to break up and reorganize multiple UAV groups, the proposed controller is designed based on the time-varying network topology. It is proved that the closed-loop system is uniformly asymptotically stability. Simulation and experiment results indicate that the proposed strategy can achieve formation control of multiple UAVs under safety constraints based on the measurement of relative measurement information.

Disturbance observer–based finite‐time fault tolerant control of quadrotor unmanned aerial vehicles with command filtered and event‐triggered techniques

AbstractThis article primarily focuses on the finite‐time fault‐tolerant tracking control problem of quadrotor unmanned aerial vehicle (UAV) systems. Our main innovation points are: (1) A simple cubic form of Lyapunov function is applied to the design of the position ring controller of the quadrotor UAV; (2) The command filtering technology effectively solves the challenge of derivation of complex coupling matrixs in the controller design process; (3) An improved disturbance observer and a variable threshold event‐triggered mechanism are applied in the Quadrotor UAV system. In summary, the overall approach combines the backstepping method and finite‐time Lyapunov stability to prove the finite‐time stability of all the signals in the system. Finally, the effectiveness and rationality of the algorithm are verified through simulation experiments and its application on an actual simulation platform.

Fixed-time trajectory tracking control of a quadrotor UAV under time-varying wind disturbances: theory and experimental validation

This paper adopts a fixed-time method to study the trajectory tracking issue of a quadrotor unmanned aerial vehicle (UAV) under time-varying wind disturbances. Firstly, in order to address the impact of time-varying wind disturbances on UAV, a fixed-time disturbance observer is constructed to accurately estimate wind disturbances. Secondly, to improve control accuracy and convergence rate, a robust fixed-time controller is designed for the position and attitude system by combining the sliding mode control theory with fixed-time techniques. Furthermore, it is rigorously analyzed that the tracking error of the observer and controller can converge to zero via Lyapunov criterion, and the convergence time is independent of the initial state. Finally, the effectiveness and robustness of the designed control strategy are verified by numerical simulations and actual flight experiments, providing an effective connection between control theory and practical applications.

Observer based attack detection and security control for UAVs against attacks on desired trajectory

This paper investigates an attack detection and security control strategy for unmanned aerial vehicles (UAVs) in the presence of malicious attacks. The detection, estimation, and compensation of the attack are the key points of the proposed scheme. This article considers that the desired trajectory sent by the ground control station (GCS) to the UAV is maliciously tampered with. First, a description of the UAV system and the desired trajectory attack is presented. The mathematical model is constructed by analyzing the characteristics of the desired trajectory attack. Secondly, an unknown input observer (UIO) is designed to generate the state estimation error. The attack detection framework is constructed by taking into account the state estimation error and the trajectory tracking error. Thirdly, an attack estimation observer with a prescribed H∞ performance is designed to compensate for the impact of attacks on the control system. A disturbance observer (DO) is used to compensate for the system disturbance. Finally, the simulation results are presented on Matlab and Gazebo to validate the effectiveness of the proposed security control strategy.

Effect of interface design on cognitive workload in unmanned aerial vehicle control

Unmanned Aerial Vehicle (UAV) control interfaces are critical channels for transferring information between the vehicle and an operator. Research on system performance has focused on enhancing vehicle automation and some work has evaluated cognitive workload for existing UAV interfaces. The potential for usable interface design to reduce cognitive workload during the early design phase has been largely overlooked. This study addresses these gaps by: (1) evaluating the effectiveness of a contemporary UAV interface design tool (the Modified GEDIS-UAV) to moderate user workload; (2) examining the effectiveness of various UAV interface designs for minimizing cognitive workload under different control task pacing; and (3) exploring the use of eye tracking measures, traditionally applied in other domains, as indicators of cognitive workload in UAV operations. We prototyped three different interface designs, classified as “baseline”, “enhanced” and “degraded” interfaces. Cognitive workload in UAV operation was manipulated in terms of levels of vehicle speed (“low” and “high”). Physiological and subjective measures of workload were collected for all combinations of interface design and task demand. Results revealed the “enhanced” interface to yield the lowest operator cognitive workload and supported operator resilience to increased control task demand, as compared to the “baseline” and “degraded” interfaces. In addition, task demand was found to elevate operator cognitive workload, particularly in terms of "mental" and "temporal" demands and operator perceptions of "performance". The study also demonstrated utility of eye-tracking technology for detecting cognitive workload in UAV operations. This research provides practical guidance for UAV control interface design to manage operator workload. The methods employed in the study are applicable to interface evaluation for various types of UAVs and other unmanned systems to enhance human-automation interaction.

Prescribed Performance Fault-Tolerant Attitude Tracking Control for UAV with Actuator Faults

This paper proposes a prescribed performance fault-tolerant control based on a fixed-time extended state observer (FXTESO) for a carrier-based unmanned aerial vehicle (UAV). First, the attitude motion model of the UAV is introduced. Secondly, the proposed FXTESO is designed to estimate the total disturbances including coupling, actuator faults and external disturbances. By using the barrier Lyapunov function (BLF), it is proved that under prescribed performance control (PPC), the attitude tracking error is stable within the prescribed range. The simulation results for tracking the desired attitude angle show that the average overshoot and stabilization time of PPC-FXTESO is 0.00455rad and 6.2s. Comparatively, the average overshoots of BSC-ESO and BSC-FTESO are 0.035rad and 0.027rad, with stabilization times of 14.97s and 12.56s, respectively. Therefore, the control scheme proposed in this paper outperforms other control schemes.

UAV formation control using enhanced behavior mechanism and artificial potential field

Inspired by formation flight of pigeon flock, this paper proposes a enhanced method of autonomous formation control of multiple Unmanned Aerial Vehicles (UAVs) that can maintain high symmetry based on pigeon flock behavior mechanism. Addressing the instability of formation in the original method, the follow improvements have been made. Firstly, improve leadership of top three UAVs, Secondly, modify artificial potential field strategies for top two followers. Finally, through a series of simulation experiments, it is verified that the UAVs can form the expected formation under the autonomous formation control, and can maintain the formation under the complex motion of leader UAV.

Consensus Tracking Control of Multiple Unmanned Aerial Vehicles Subject to Distinct Unknown Delays

This article deals with the consensus tracking problem for multi-agent systems (MAS) under the influence of unknown time-varying delays. Each agent of the MAS is a quadrotor unmanned aerial vehicle (UAV) represented as a linear continuous-time system. The main objective of this paper is the stabilization of multi-agent systems where the control input is affected by unknown time-varying delays, which are assumed to be upper-bounded, and where these bounds are not required to be known. The proposed observer-based control scheme guarantees the consensus tracking of multi-UAV systems with the desired H∞ performance, which adds a further level of mitigation of unknown delays present in MAS systems by minimizing the H∞ norm, which measures the maximum gain from the disturbance to the controlled output of the system. For each UAV agent, an unknown input observer is employed to isolate the unknown time-varying delays in the state estimation process. With the use of an unknown input observer-based consensus tracking control, sufficient conditions are derived to ensure that all follower UAVs can reach a consensus with the leader, despite the presence of distinct unknown time-varying delays. The stability of the proposed scheme is proven using Lyapunov theory for the leader and follower agents. Finally, numerical examples are provided to illustrate the effectiveness of the proposed method.

Secure Communication Between Unmanned Aerial Vehicle and Ground Control Station

Secure Communication Between Unmanned Aerial Vehicle and Ground Control Station

Safe formation control of multiple unmanned aerial vehicles: control design and safety-stability analysis

Safe formation control of multiple unmanned aerial vehicles: control design and safety-stability analysis

Dynamics Event-Triggered-Based Time-Varying Bearing Formation Control for UAVs

This article addresses the leader-follower formation maneuver control problem of multiple unmanned aerial vehicles (UAVs), taking into account the time-varying velocity and time-varying relative bearing. An event-triggered bearing-based distributed velocity observer was designed, using only the desired position and velocity of the leaders. Furthermore, a dynamic event-triggered mechanism was introduced to reduce continuous communication between UAVs, thus effectively saving communication bandwidth and resources. Building on this, a bearing-only formation maneuver control strategy was proposed, integrating the event-triggered velocity observer with the backstepping control approach. To conclude, numerical simulations have been conducted to confirm the effectiveness of the proposed scheme in accomplishing formation maneuver control objectives, including translation, scaling, and rotation control. Furthermore, the advantages of the dynamic event-triggering strategy have been demonstrated through comparative simulations with traditional event-triggering strategies. Additionally, the effectiveness of the proposed observer and controller has been demonstrated by a comprehensive hardware-in-the-loop (HITL) simulation example.

Image fusion algorithm for the collaborative use of unmanned aerial vehicles

Currently, the applicable scope of unmanned aircraft application is increasingly expanding. The promising field of unmanned aircraft enhancement is the implementation of some collaborative actions during controlled flight. This paper considers some issues of the group application of unmanned aerial vehicles (UAV) related to the coordinated planning and control of UAVs performing surveillance missions. Performing aerial search operations is technically complicated by the requirement to recognize a search object in arbitrary conditions, which can be both simple and severe environment. The search area is limited by the UAV capabilities, so, in order to improve the efficiency of search operations, UAVs are combined into groups. An algorithm for solving the problem of object search in arbitrary conditions by a group of unmanned aircraft is proposed. The advantage of search by a group of unmanned aircraft is the coverage of the larger search area in a conventional unit of time. This paper addresses the unmanned aircraft configuration, containing both the means of collaborative flight operation and a synthetic vision system. The image obtained by the synthetic vision system is both a source of navigation information and a means which reliably determines the result of search operations. Depending on the conditions of search operations, the image obtained by the synthetic vision system may require additional processing to use as intended. A fusion algorithm is proposed, which is characterized by adaptive adjustment of parameters in each frame individually for different image fragments. Based on the results obtained, it is planned to create a new product for commercial operation of unmanned aircraft.

Formation of flight zones of UAV according to the degree of stability in order to increase the reliability of the command radio control line in the conditions of the use of air defense and electronic suppression

The combat use of small and medium-class unmanned aerial vehicles (UAVs) in recent local military conflicts, as well as the experience of using UAVs in the operation of the Russian Aerospace Forces in Syria and Ukraine, has shown that they are mainly assigned the tasks of aerial reconnaissance in those areas of the theater of operations (Theater of Operations) where The use of manned aircraft is unjustified or impractical due to the high probability of damage to manned aircraft. The main threats to UAVs in modern theater are the possibility of hitting them with anti-aircraft missile systems (SAMs) of air defense (air defense), as well as the suppression of the command radio control line (CRU) of the UAV by means of electronic suppression (RAP) of the enemy. The purpose of the work is to develop theoretical solutions aimed at the formalized formation of air defense and RAP zones in the theater based on clustering theory methods for subsequent consideration of these zones in the automated formation of UAV flight routes. The paper proposes a methodology for the formalized formation of air defense and RAP zones based on the methods of clustering theory. In the future, the air defense and RAP zones are taken into account in the automated route control of the UAV by forming the flight route of the UAV bypassing these zones. The novelty of this solution, which distinguishes it from well–known works in the field of formation of UAV flight routes, is the consideration of two types of destabilizing factors as obstacles to UAV flight - the impact of air defense and REP means. These factors are formalized in the form of an integral metric of nodes in the graph of the geotopological model of the theater flight zone. At the same time, the Lance-Williams mathematical algorithm of hierarchical clustering is used to form «closed for flights» zones in which the probability of UAV damage is high, and areas of control violation due to the impact of RAP means. The connectivity check of the route network is based on the method of determining the strongly connected areas of the graph. The resulting solution makes it possible to increase the stability of UAV control during their combat use in theater equipped with air defense and RAP systems.

Heterogeneous unmanned swarm formation containment control based on reinforcement learning

In response to the problem of time-varying spherical formation control for a heterogeneous unmanned aerial vehicle (UAV) swarm system with dynamic uncertainty in the system model, this paper proposes an optimal distributed formation containment control method based on reinforcement learning. By combining the time-varying formation containment vector design with the distributed predefined time observer and constructing the augmented system of a multi-quadrotor UAV system and an observer, the problem of time-varying formation containment control in heterogeneous swarm systems is transformed into a stabilization problem. By introducing a value function with a discount factor, the stabilization problem of a heterogeneous UAV swarm system is transformed into an optimal control problem. Using the “actor-critic” neural network, combined with an off-policy reinforcement learning algorithm and distributed control methods, the solution to the formation containment controller is achieved in a data-driven manner. The stability of distributed observer and formation containment controller as well as the convergence of reinforcement learning algorithms are demonstrated using Lyapunov and related theory. The numerical simulation results demonstrate that the observation error of the designed distributed observer converges within a predefined time of 0.1 s, while the overall formation tracking error of the heterogeneous swarm converges within 2.74 s, thereby further validating the effectiveness and superiority of the designed control scheme.

Planar curved path following controller for a small fixed-wing unmanned aerial vehicle with constrained parameters optimized by nonlinear model predictive control

Path following presents a pivotal challenge within the realm of small fixed-wing unmanned aerial vehicles. Firstly, a Lyapunov-stable path guidance law was formulated to follow specific planar curved paths. To ensure differentiability of the guidance law, a modified, smooth saturation function was derived. Secondly, an analysis was conducted to ascertain the interrelationship between control parameters and input constraints, thereby identifying the relevant parameter domains. Thirdly, the nonlinear model predictive control technique was harnessed to optimize both guidance law parameters, enhancing the unmanned aerial vehicle’s capacity to achieve optimal performance in both straight-line and circular path following, hereafter referred to as PFC_NMPC. By leveraging Lyapunov stability arguments for switched systems, the stability of the corresponding nonlinear switched system was guaranteed. In this study, square and circular paths were generated to assess the path-following control of a simulated fixed-wing unmanned aerial vehicle. The performance of various guidance laws, including those with fixed parameters (PFC), those with parameters tuned using fuzzy logic (PFC_FL), PFC_NMPC, vector field, and pure pursuit with line-of-sight, was compared. Notably, the proposed PFC_NMPC method exhibited the ability to expedite the unmanned aerial vehicle’s convergence to the desired path while maximizing the effective flight path length.

Attack Detection and Security Control for UAVs Against Attacks on Desired Trajectory

The paper presents a security control scheme for unmanned aerial vehicles (UAVs) against desired trajectory attacks. The key components of the proposed scheme are the attack detector, attack estimator, and integral sliding mode security controller (ISMSC). We focus on malicious tampering of the desired trajectory sent by the ground control station (GCS) to the UAV by attackers. Firstly, we model attacks by analyzing the characteristics of desired trajectory attacks. Secondly, an integrated attack detection scheme based on an unknown input observer (UIO) and an interval observer is presented. Subsequently, a robust adaptive observer (RAO) is employed to compensate for the impact of attacks on the control system. Thirdly, an ISMSC with an attack compensation mechanism is established. Finally, simulation results are provided to verify the effectiveness of the proposed scheme. The proposed detection scheme can not only detect desired trajectory attacks but also distinguish them from abrupt unknown disturbances (AUDs). By utilizing ISMSC method, UAVs under desired trajectory attacks can fly safely. The proposed comprehensive framework of detection, estimation and compensation provides a theoretical basis for ensuring cyber security in UAVs.

Adaptive Controller Based on Estimated Parameters for Quadcopter Trajectory Tracking

This paper presents a trajectory control system design for a quadcopter, an unmanned aerial vehicle (UAV), which is based on estimated parameters that are assumed to exhibit random walk behavior. Initially, the rotational dynamic model of the UAV is formulated using the Newton Euler method in terms of angular velocity about the x, y, and z axes. This model is then simplified into three separated-first-order linear differential equations, with coefficients derived from the combined effects of inertia, aerodynamic drag, and gyroscopic effects, referred to as lumped parameters. A Proportional-Integral (PI) controller with feed-forward design is then developed to control this simplified model. To adapt the controller to the lumped parameters that exhibit random walk behavior, each simplified equation is restructured into a processing and measurement model. The states of these models are estimated by using the Unscented Kalman Filter (UKF). These estimated values are then utilized to adjust the PI gains and compensate the signal of the designed angular velocity controller, transforming it into an adaptive controller. The entire UAV controller comprises two main parts, an inner loop for adaptive angular rate control and an outer loop serving as an attitude-thrust controller. The proposed controller is simulated using Simulink, with circular and square trajectories. The simulation results demonstrate that the quadcopter successfully follows the desired circular and square paths. The steady-state error for the x and y axes in the square trajectory is less than 0.05 meters within 5 seconds, and for the z axis, it is less than 0.02 meters within 2.5 seconds. The controller gains do not require adjustment when changing trajectories. Moreover, the estimated parameters remain nearly constant at steady state.

Monitoring the State of the Operator of the Ergatic System in UAV Control Tasks

An important aspect of the application of unmanned systems is the reliability and safety of controlling these devices. An innovative approach has been proposed to improve the efficiency of the pilot operator and the reliability of the automated control system. It includes the development of an algorithm for determining the pilot’s condition based on heart rate analysis. This algorithm helps to assess the condition of the pilot and his ability to control the drone. Another important element of the proposed approach is the algorithm for selecting the control mode of the automated control system for unmanned aerial vehicles, which takes into account information about the functional state of the pilot operator. This algorithm allows the system to automatically switch between different operating modes depending on the condition of the pilot, ensuring optimal control and minimizing the risks of human error. An integrated approach to improving the reliability of the unmanned aerial vehicle control system allows not only improving the work of the pilot operator, but also ensuring the safer and more efficient operation of automated systems.

UAV control in autonomous object-goal navigation: a systematic literature review

Research interest in autonomous control of unmanned aerial vehicles (UAVs) has increased rapidly over the past decade. They are now widely used in civilian, military, and private areas. Applications include surveillance, search and rescue, and delivery tasks. More broadly, they excel at solving problems where a significant amount of space must be covered and traveled. However, using UAVs to solve navigation problems with full autonomy necessitates the mastering of complex subtasks. A solution that includes control, planning, localization, and mapping remains an open challenge. Object-goal navigation contains the same navigation problems where the main objective is to reach a target object. The search and identification of this target are central to the vehicle’s navigation. This requires an understanding of what it is and where it can be located to move around the scene. This paper presents a systematic literature review on object-goal navigation and its subtasks, using autonomous UAVs. Survey taxonomies were found for the tasks and methods behind navigation and target localization problems using UAVs. The review analyzed 67 articles found between 2011 and 2022. They were found in the ACM, IEEE Xplore, WebOfScience, Science Direct, and Scopus databases. This review revealed essential issues related to autonomous navigation task dependencies. Moreover, it highlighted gaps in UAV development and framework standardization. Open challenges for autonomous UAV control for object-goal navigation must address the research on finding methods for problems. For example, autonomy level and comparison metrics, considering safety, ethics, and legal implications.