Synthesis of a controller for quadrotors with suspended payloads

Intelligent control of an UAV with a cable-suspended load using a neural network estimator

In this paper, a fractional Active Disturbance Rejection Control (ADRC) is proposed to track the desired trajectory workspace and solve the attitude control problem of a quadcopter Unmanned Aerial Vehicle (UAV). The ADRC is a robust nonlinear control being used recently to control the UAV technologies. It is mostly used to solve the major key challenges related to uncertainties, imperfect modeling, and external disturbances in a simple structure and easy way in control parameters tuning. The main idea of the ADRC control strategy is to introduce a fictitious state variable that represents the total disturbance. Then, this disturbance is estimated via an Extended State Observer (ESO). The estimated disturbance is fed back to construct a suitable controller, and hence decouple the system from all uncertainties and disturbances acting on the plant. A fractional State Error Feedback (SEF) controller is implemented and compared with the traditional SEF to enhance the system performance. Simulation results demonstrate the robustness and effectiveness of the proposed fractional control strategy in tracking the desired trajectory in the workspace of the quadcopter UAV.

In this paper, aiming to drive the unmanned aerial vehicle (UAV) to the optimal position of the vertical plane in the close formation flight, a control method that is based on extended state observer (ESO) and wingtip vortex structure is proposed. This method is suitable for cases where the optimal position is unknown and there are gusts. The scheme is divided into three parts. In the first part, an ESO is designed to estimate the change of the lift and other external disturbances on the follower UAV. In the second part, an algorithm making use of the estimates of the change of the lift to predict the optimal position for the follower UAV is proposed. In the third part, to stabilize the UAV around the optimal position, a sliding mode controller is designed and the external disturbances on the follower UAV are compensated by the ESO. The simulation results show that the followers could automatically adjust their spatial positions to track the predicted optimal positions behind the leader UAV and achieve the precisely close formation flight without the information of leader’s altitude.

Time-varying formation tracking problem for unmanned aerial vehicle (UAV) swarm systems subject to unknown nonlinear dynamics, external disturbances, and switching topologies is studied. The states of the following UAV s are required to form a predefined time-varying formation while tracking the state of the leading UAV. For each following UAV, the unknown nonlinear dynamics and external disturbance are regarded as an extended state of the UAV, and then an extended state observer (ESO) is correspondingly designed. Based on the output of the ESO, a novel time-varying formation tracking protocol is proposed. Rigorous theoretical analysis is given to show that, with the application of the proposed protocol, the ESO estimation error and the time-varying formation tracking error can be made arbitrarily small. A numerical simulation demonstrates the effectiveness of the proposed approach.

This paper addresses the problem of point-to-point path planning of a 3D model of a quadcopter carrying a suspended load by parameterizing its differentially flat outputs. The flat outputs are the Cartesian coordinates of the suspended load and the yaw angle of the quadcopter. The time integral of the absolute angular rate of the suspended load is minimized to synthesize a trajectory which minimizes the pendular oscillations of the suspended load while the quadcopter transition from one point of rest to another. An established feedback controller and an input shaped profile for the closed loop system dynamics using position as reference and also velocity as reference are also developed to compare the performance of the proposed controller. Experimental results validate results obtained via simulation showing that the differential flat solution outperforms the pure feedback and the feedback system with input shaping prefilters.

In current flight control system (FCS) practice for unmanned aerial vehicles(UAVs), flight safety becomes more and more important in extreme weather or in the face of sensor and control effector failures. Flight safety is guaranteed traditionally by specifying functionally redundant control hardware. Compared with extra burden increased by hardware redundancy on UAV, design of analytical redundancy becomes attractive in recent years. This paper proposes a new hybrid design scheme of analytical redundance FCS, which is composed of analytical redundance, core flight control algorithm and uncertainties compensator. Analytical redundancy for attitude angle rates adopts reduced order nonlinear state observer method. The core backstepping flight controller realizes linearization and decoupling of the highly nonlinear and tightly coupled UAV model. For cancelling out uncertainties such as unmodeled dynamics and external disturbances, an extended state observer(ESO) compensator is designed to enhance the robustness of FCS. Pseudoinverse method is applied to establish the mapping between moments and multiple control surfaces. Numerical simulation shows that UAV equipped with the hybrid control scheme has good maneuverability, strong self-learning ability of compensating the unmodeled dynamics and enough robust stability against constraints of actuators.

The object of research is the system determines the target angular coordinates on the missile’s homing head. Current target coordinate determination systems employed in seekers often operate under significant limitations. When a target’s actual motion deviates from the simplified, hypothetical model used to synthesize the coordinate system, a critical issue arises: the errors in evaluating both the coordinates and their derivative components rapidly and significantly increase. Problem that was solved is to evaluate complex maneuvering target parameters. But there is no need to know the target’s maneuver frequency. This study presents a novel filtering algorithm that accurately estimates all parameters of complex maneuvering targets without prior knowledge of their maneuver frequency. The algorithm achieves a significant advantage, reducing estimation error by over 95% within the first 5 seconds. With its simple structure, high stability, and fast convergence, this robust solution is essential for modern guidance systems, greatly enhancing the effectiveness of tracking unpredictable threats. A key strength of the proposed algorithm lies in its simple structure. Furthermore, it demonstrates high convergence rates and exceptional stability, crucial attributes for real-time applications. Its design also ensures ease of practical implementation, making it a viable solution for contemporary guidance systems. The algorithm is built on modern control techniques, combining extended Kalman filtering with interactive multi-models. It is necessary to accurately evaluate the target’s position, velocity, acceleration, and acceleration derivative without needing to know in advance the target’s maneuver frequency

This paper presents a decentralized approach to transport a cable suspended load using multiple Unmanned Aerial Vehicles (UAVs). The proposed approach is decentralized in the sense that the trajectory for each of the UAVs is computed offline using the kinematics of the system and the desired path of the load. This approach enabled the task of cooperative transportation to be treated as a problem of multiple UAVs, each carrying a cable suspended load. A neural adaptive sliding mode controller proposed by the authors in an earlier work is then deployed on each of the UAVs to track the trajectory while minimizing the load swing. Since the system of an UAV carrying a suspended load is underactuated, the conditions on the sliding surface variables that ensure the stability of the system are also given. The performance of the proposed approach is tested with payloads of non-uniform density and uncertain mass, using Gazebo simulations. The performance is compared against an adaptive sliding mode controller which motivated the design of the proposed controller.

PurposeThe purpose of this paper is to present an actuator fault detection method for unmanned aerial vehicles (UAVs) based on interval observer and extended state observer.Design/methodology/approachThe proposed algorithm has very little model dependency. Therefore, a six-degree-of-freedom linear equation of UAVs is first established, and then, combined with actuator failure and external disturbances in flight control, a steering gear model with actuator failure (such as stuck bias and invalidation) is designed. Meanwhile, an extended state observer is designed for fault detection. Moreover, a fault detection scheme based on interval observer is designed by combining fault and disturbances.FindingsThe method is testified on the extended state observer and the interval observer under the failure of the steering gear and bounded disturbances. The simulation results show that the two types of fault detection schemes designed can successfully detect various types of faults and have high sensitivity.Originality/valueThis research paper studies the failure detection scheme of the UAVs’ actuator. The fault detection scheme in this paper has better performance on actuator faults and bounded disturbances than using regular fault detection schemes.

In order to overcome the influence of internal and external disturbances caused by rotor tilt motion and gust disturbance on the full flight mode control of a tilt-rotor unmanned aerial vehicle (UAV), a design method using fuzzy backstepping control based on an extended-state observer (FBS-ESO) is proposed. In this paper, fuzzy control is used to tune the parameters of the backstepping control law online, and the extended-state observer estimates the total disturbance of the controlled system to improve the controller’s robustness and anti-disturbance capability. This paper designs the attitude control system of a tilt-rotor UAV based on an FBS-ESO controller. The control performance of the FBS-ESO controller is tested in a hardware-in-loop simulation of the attitude control system. The simulation results show that changing the rotor tilt angle will destroy the stability of the traditional backstepping controller and active disturbance rejection controller (ADRC). In contrast, the FBS-ESO controller maintains good control performance. In addition, the performance of the FBS-ESO controller is not be significantly affected by adding external gust disturbance or changing the UAV parameters in the simulation. These disturbances significantly impact the traditional backstepping controller and ADRC. Therefore, the FBS-ESO controller has better anti-disturbance capabilities and robustness, as well as higher attitude control accuracy.

A robust feedback linearization controller is presented for attitude control of an Unmanned Aerial Vehicle (UAV). The objective of this controller is to make the roll angle, pitch angle, and yaw angle track the given trajectories(commands) respectively. This design is developed using dynamic inversion and extended state observer (ESO).Firstly, dynamic inversion is used to linearize and decouple UAV attitude system into three single-input-single-output (SISO)systems, then three proportional-derivative (PD) controllers are designed for these linearized systems. Extended state observers are used to estimate and compensate unmodeled dynamics and extern disturbances. Simulation results show that the proposed controller is effective and robust.

Quad-rotor unmanned aerial vehicle (UAV) is a typical multiple-input-multiple-output underactuated system with couplings and nonlinearity. Usually, the flying environment is very complex, so that it is impossible for the UAV to avoid effects derived from disturbances and uncertainties. In order to improve the reliability of flight control, we established the dynamic model of quad-rotor UAV by Newton-Euler equation in unbalanced load conditions. Considering external disturbances in the attitude, a second-order sliding mode controller was designed with PID sliding mode surface and Extended State Observer (ESO). The simulation experiments have got good control performance, illustrating the effectiveness of our controller. Meanwhile, the controller was implemented in a quad-rotor UAV, which carried a pan-tilt camera for aerial photography. The actual flight experiments proved that this paper dealt with the high stabilization flight control problem for the quad-rotor UAV, which laid a good foundation for autonomous flight of the UAV.

In the field of logistics transportation, unmanned aerial vehicles are commonly utilized for cargo transport in a suspended manner, and the suspended payloads will exhibit the double‐pendulum dynamic characteristics (dPDC). However, due to the underactuation and load‐swing problems caused by the dPDC, it is challenging to design controllers for a quadrotor with a suspended double‐pendulum type payload. Existing related studies simplify the dPDC to a single‐pendulum dynamic characteristic, which results in degraded transient performance. To overcome the issue, this article presents a novel controller approach that considers the real dynamic characteristics, that is, dPDC. The proposed approach tackles the quadrotor position control and anti‐swing problem in two steps. First, a composite signal incorporating both the quadrotor position and the payload swing angles is introduced to restrain the payload swing. Second, a nonlinear controller based on the energy analysis method is proposed to overcome the coupling between rotation and translation, which addresses the underactuation problem. Theoretical analysis confirms the asymptotic stability of the system under this control strategy. Numerical and experimental results are provided to demonstrate the effectiveness of the proposed controller.

Nowadays, aerial robots or Unmanned Aerial Vehicles (UAV) have many applications in civilian and military fields. For example, of these applications is aerial monitoring, picking loads and moving them by different grippers. In this research, a quadrotor with a cable-suspended load with eight degrees of freedom is considered. The purpose is to control the position and attitude of the quadrotor on a desired trajectory in order to move the considered load with constant length of cable. So, the purpose of this research is proposing and designing an antiswing control algorithm for the suspended load. To this end, control and stabilization of the quadrotor are necessary for designing the antiswing controller. Furthermore, this paper is divided into two parts. In the first part, dynamics model is developed using Newton-Euler formulation, and obtained equations are verified in comparison with Lagrange approach. Consequently, a nonlinear control strategy based on dynamic model is used in order to control the position and attitude of the quadrotor. The performance of this proposed controller is evaluated by nonlinear simulations and, finally, the results demonstrate the effectiveness of the control strategy for the quadrotor with suspended load in various maneuvers.

Our study is concerned with the time-varying formation tracking problem for second-order multi-agent systems that are subject to unknown nonlinear dynamics and external disturbance, and the states of the followers form a predefined time-varying formation while tracking the state of the leader. The total uncertainty lumps the unknown nonlinear dynamics and the external disturbance, and is regarded as an extended state of the agent. To estimate the total uncertainty, we design an extended state observer (ESO). Then we propose a novel ESO based time-varying formation tracking protocol. It is proved that, under the proposed protocol, the ESO estimation error and the time-varying formation tracking error can be made arbitrarily small. An application to the target enclosing problem for multiple unmanned aerial vehicles (UAVs) verifies the effectiveness and superiority of the proposed approach.