Swarms of unmanned aerial vehicles — A survey

Emerging applications of quadrotor vertical take-off and landing (VTOL) unmanned aerial vehicles in various fields have created a need for demanding controllers that are able to counter several challenges, inter alia, nonlinearity, underactuated dynamics, lack of modeling, and uncertainties in the working environment. This study compares and contrasts type-1 and type-2 fuzzy neural networks (T2FNNs) for the trajectory tracking problem of quadrotor VTOL aircraft in terms of their tracking accuracy and control efforts. A realistic trajectory consisting of both straight lines and curvatures for a surveillance operation with minimum snap property, which is feasible regarding input constraints of the quadrotor, is generated to evaluate the proposed controllers. In order to imitate the outdoor noisy and time-varying working conditions, realistic uncertainties, such as wind and gust disturbances, are fed to the real-time experiment in the laboratory environment. Furthermore, a cost function based on the integral of the square of the sliding surface, which gives the optimal parameter update rules, is used to train the consequent part parameters of the T2FNN. Thanks to the learning capability of the proposed controllers, experimental results show the efficiency and efficacy of the learning algorithms that the proposed T2FNN-based controller with the optimal tuning algorithm is 50% superior to a conventional proportional-derivative (PD) controller in terms of control accuracy but requires more control effort. T2FNN structures are also shown to possess better noise reduction property as compared to their type-1 counterparts in the presence of unmodeled noise and disturbances.

Type-2 Fuzzy Logic Trajectory Tracking Control of Quadrotor VTOL Aircraft With Elliptic Membership Functions

Quadrotor a kind of multirotor unmanned air vehicle has gained popularity within research community due to its high manoeuvrability, vertical take-off, landing and hovering capability, and ease of operation in areas where traditional unmanned air vehicle have proved ineffective. This article provides a comprehensive survey of research methodologies proposed for quadrotor control. The methodologies are categorised into three different control design domains and each methodology is discussed in detail. Finally, we discuss the evaluation criteria used for the aforementioned methodologies and highlight the potential challenges that still need to be addressed in quadrotor control domain.

A review of quadrotor UAV: control methodologies and performance evaluation

We present a robust adaptive second-order sliding mode controller that rejects external disturbances and uncertainties to improve the tracking performance of attitude and altitude in a quadcopter based on a Proportional–Integral–Derivative sliding surface. The algorithm provides a rapid adaptation and strict robustness of the flight control for the vehicle under the effect of perturbations. The proposed controller design is based on the theory of second order sliding mode technique that eliminates the chattering phenomenon present in first-order sliding mode controllers. In addition, we derive an adaptive law from the Lyapunov stability to ensure the robust control for the quadcopter even without knowing the upper bound for disturbances. Applying the same external disturbances, we use a numerical simulation to compare our algorithm to recent alternatives, such as normal adaptive sliding mode control, super-twisting sliding mode control, modified super-twisting sliding mode control, and nonsingular terminal sliding mode control. The results demonstrate the effectiveness of our proposed algorithm.

Quadcopter Robust Adaptive Second Order Sliding Mode Control Based on PID Sliding Surface

In this paper, a cascade PID feedback control algorithm is proposed to stabilize the attitude of a quadcopter so that the balancing state can be ensured in spite of disturbances. A mathematical model of quadcopter dynamics is developed by applying Newton-Euler method. It reveals the exact relationships among all the variables involved. Both linear and nonlinear state-space equations are derived afterwards, which are essential for the controller design and further development. The simulations are also carried out to demonstrate the effectiveness and robustness of the cascade PID algorithm compared with classic PID control scheme.

Dynamics modelling and linear control of quadcopter

This paper aims to present a comparison between different controllers to be used in a dynamic model of a quadcopter platform. The controllers assumed in this work are an ITAE tuned PID, a classic LQR controller and a PID tuned with a LQR loop. The results were obtained through simulations for 10 different attitudes of the quadcopter, however, in this paper simulation results will be presented for the vertical attitude only (the remainder are analogous and were omitted for brevity).

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Willian C. Rezende

Papers

PID, LQR and LQR-PID on a quadcopter platform