Event-triggered discrete extended state observer–based model-free controller for quadrotor position and attitude trajectory tracking

In this article, an event-triggered discrete extended state observer–based model-free controller is developed for the position and attitude trajectory tracking of a quadrotor with uncertainties and external disturbances. The referred event-triggered discrete extended state observer–based model-free controller is composed of two event-triggered mechanisms, ultra-local model-based discrete extended state observer and proportional-derivative sub-controller. To reduce system output signal transmission, the event-triggered mechanism of output signal which owns dynamic and static threshold is designed. Based on event-triggered output signals, the discrete extended state observer is constructed to obtain the estimations of state values which are utilized as controller’s variables and to compensate for the lumped disturbances. The proportional-derivative sub-controller is adopted to guarantee the convergence of trajectory tracking error. To decrease control input signal transmission, the event-triggered mechanism of input signal that processes static threshold is constructed. Moreover, the stability analysis of overall quadrotor system with the proposed control strategy is investigated using Lyapunov theorem and the Zeno behavior is avoided. Finally, corresponding control scheme for quadrotor system is structured and the numerical comparative simulation and co-simulation experiment are given to demonstrate the effectiveness and performance of the proposed approach.

Autonomous landing of a quadrotor on a moving platform using vision-based FOFPID control

This research deals with the autonomous landing maneuver of a quadrotor unmanned aerial vehicle (UAV) on an unmanned ground vehicle (UGV). It is assumed that the UGV moves independently, and there is no communication and collaboration between the two vehicles. This paper aims at the design of a closed-loop vision-based control system for quadrotor UAV to perform autonomous landing maneuvers in the possible minimum time despite the wind-induced disturbance force. In this way, a fractional-order fuzzy proportional-integral-derivative controller is introduced for the nonlinear under-actuated system of a quadrotor. Also, a feedback linearization term is included in the control law to compensate model nonlinearities. A supervisory control algorithm is proposed as an autonomous landing path generator to perform fast, smooth, and accurate landings. On the other hand, a compound AprilTag fiducial marker is employed as the target of a vision positioning system, enabling high precision relative positioning in the range between 10 and 350 cm height. A software-in-the-loop simulation testbed is realized on the windows platform. Numerical simulations with the proposed control system are carried out, while the quadrotor system is exposed to different disturbance conditions and actuator dynamics with saturated thrust output are considered.

Quadrotor Controller Design Techniques and Applications Review

Rotor-craft style UAV, such as the quadrotor, has become increasingly popular with researchers due to its advantages over fixed-wing UAV. The quadrotor is highly maneuverable, can perform vertical take-off and landing (VTOL), and can hover flight capability. Nevertheless, handling the quadrotor complex, highly nonlinear dynamics is difficult and challenging. A suitable control system is needed to control the quadrotor system effectively. Therefore, this paper presents a review of different controller design techniques used by researchers over the past years for the quadrotor rotational and translational stabilization control. Three categories are discussed: linear controller, nonlinear controller, and intelligent controller. Based on their performance specifications, the system rise time, settling time, overshoot, and steady-state error are discussed. Finally, a comparative analysis is tabulated, summarizing the literature in the performance specifications described above.

PID Controllers Design for a Quadrotor System Using Teaching Learning Based Optimization

Optimized Proportional Integral Derivative controllers are designed to control the translational and rotational motions of a quadrotor system with six degrees of freedom. The teaching learning based optimization algorithm is used to obtain the proportional, integral and derivative gains of six PID controllers so that the integral time absolute error criterion is minimized. The control objective, is to enforce the horizontal position, altitude and yaw angle of the quadrotor to track their desired reference trajectories while stabilizing its roll and pitch angles. The efficiency and the control performance of the proposed scheme are demonstrated through numerical simulation and compared with those of the PID controllers designed using genetic algorithm, the sliding mode control and other control techniques proposed in the literature. The simulation study shows the good performance of the proposed control scheme in terms of transient response characteristics, tracking accuracy and disturbance rejection.

Robust Discrete-Time Nonlinear Attitude Stabilization of a Quadrotor UAV Subject to Time-Varying Disturbances

A discrete-time improved input/output linearization controller based on a nonlinear disturbance observer is considered to secure the stability of a four-rotor unmanned aerial vehicle under constant and time-varying disturbances, as well as uncertain system parameters for its attitude behaviour. Due to the nature of the quadrotor system, it contains the most extreme high level of nonlinearities, system parameter uncertainties (perturbations), and it has to cope with external disturbances that change over time. In this context, an offset-less tracking for the quadrotor system is provided with the input/output linearization controller together with a discrete-time pre-controller. In addition, the robustness of the system is increased with a discrete-time nonlinear disturbance observer for time-varying disturbances affecting the system. The main contribution of this study is to provide highly nonlinearities cancellation to guarantee the aircraft attitude stability and to propose a robust control structure in discrete-time, considering all uncertainties. Various simulation studies have been carried out to illustrate the robustness and effectiveness of the proposed controller structure.

Development of Multi-Quadrotor Simulator Based on Real-Time Hypervisor Systems

Today, simulator technology has been widely used as an important part of quadrotor development such as validation and testing. A good quadrotor simulator can simulate the quadrotor system as closely as possible to the real one. Therefore, in case of multi-quadrotor simulator, the simulator should not only can simulate a multi-quadrotor system, but also every quadrotor should be able to leverage their own resources. To solve this issues, in this paper, we present a hypervisor-based multi-quadrotor simulator. We used RT-Xen as hypervisor, a real-time Xen hypervisor. To ensure every quadrotor runs in real-time manner, we implemented quadrotor simulator in Litmus-RT which is a real-time extension of Linux. In this paper, we conducted some testing and performance evaluation for particular cases on our multi-quadrotor simulator: step-input responses, computation time, and response times. Based on the performance evaluation, our hypervisor-based multi-quadrotor simulator environment is proven to meet the real-time requirements. The results show that three important tasks in quadrotor system: Stability Controllability Augmented System (SCAS), Equation of Motion (EOM), and waypoint following task, are finished before their deadlines; in fact, 20 ms, 10 ms, and 40 ms before the deadlines for SCAS, EOM, and waypoint following, respectively.

Embedded linear model predictive control in field-programmable gate array using register-transfer level implementation and floating-point representation applied to a quadrotor system model

Model predictive control is increasingly becoming a popular control strategy for a wide range of applications in both industry and academia, mainly motivated by its ability to systematically handle constraints imposed on a system, regardless of its nature. However, this generates high computational demands, limiting the applicability of model predictive control. Field-programmable gate arrays are reconfigurable hardware platforms that allow the parallel implementation of model predictive control, accelerating such algorithms, but most works found in the literature opt to use high-level synthesis tools and fixed-point numeric representation to generate embedded controllers, resulting in faster-designed solutions but not exactly efficient and flexible ones, that can be applied to different scenarios. Regarding such matter, this work proposes the manual implementation (register-transfer level implementation) of linear model predictive control and the usage of floating-point numeric representation applied to a quadrotor system. The initial results obtained using the proposed controller are presented in this article, achieving 29.34 ms of calculation time at 50 MHz for the attitude control of a quadrotor model containing twelve states and four control outputs.