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The purpose of this paper is to propose a new approach for robust control of an autonomous quadrotor unmanned aerial vehicle (UAV) in automatic take-off, hovering and landing mission and also to improve the stabilizing performance of the quadrotor with inherent time-varying disturbance.

First, the dynamic model of the aerial vehicle is mathematically formulated. Then, a combination of a nonlinear backstepping scheme with the intelligent fuzzy system as a new key idea to generate a robust controller is designed for the stabilization and altitude tracking of the vehicle. For the problem of determining the backstepping control parameters, a new heuristic algorithm, namely, Gravitational Search Algorithm has been used.

The control law design utilizes the backstepping control methodology that uses Lyapunov function which can guarantee the stability of the nominal model system, whereas the intelligent system is used as a compensator to attenuate the effects caused by external disturbances. Simulation results demonstrate that the proposed control scheme can achieve favorable control performances for automatic take-off, hovering and landing mission of quadrotor UAV even in the presence of unknown perturbations.

This paper propose a new robust control design approach which incorporates the backstepping control with fuzzy system for quadrotor UAV with inherent time-varying disturbance. The originality of this work relies on the technique to compensate the disturbances acting on the quadrotor UAV. In this new approach, the fuzzy system is introduced as an auxiliary control effort to compensate the effect of disturbances. Because the proposed control technique has the capability of robustness against disturbance, thus, it is also suitable to be applied for a broad class of uncertain nonlinear systems.

The control of a quadrotor unmanned aerial vehicle (UAV) is a challenging problem because of its highly nonlinear dynamics, under-actuated nature and strong cross-couplings. To solve this problem, this paper aims to propose a robust control strategy, based on a concept of active disturbance rejection control (ADRC).

The altitude/attitude dynamics of a quadrotor is reformulated into the ADRC framework. Three distinct variations of the error-based ADRC algorithms, with different structures of generalized extended state observers (GESO), are derived for the altitude/attitude trajectory-following task. The convergence of the observation part is proved based on the singular perturbation theory. Through a frequency analysis and a quantitative comparison in a simulated environment, each design is shown to have certain advantages and disadvantages in terms of tracking accuracy and robustness. The digital prototypes of the proposed controllers for quadrotor altitude and attitude control channels are designed and validated through real-time hardware-in-the-loop (HIL) co-simulation, with field-programmable gate array (FPGA) hardware.

The effects of unavailable reference time-derivatives can be estimated by the ESO and rejected through the outer control loop. The higher order ESOs demonstrate better performances, but with reductions of stability margins. Time-domain simulation analysis reveals the benefits of the proposed control structure related to classical control approach. Real-time FPGA-based HIL co-simulations validated the performances of the considered digital controllers in typical quadrotor flight scenarios.

The conducted study forms a set of practical guidelines for end-users for selecting specific ADRC design for quadrotor control depending on the given control objective and work conditions. Furthermore, the paper presents detailed procedure for the design, simulation and validation of the embedded FPGA-based quadrotor control unit.

In light of the currently available literature on error-based ADRC, a comprehensive approach is applied here, which includes the design of error-based ADRC with different GESOs, its frequency-domain and time-domain analyses using different simulation of UAV flight scenarios, as well as its FPGA-based implementation and testing on the real hardware.

This study aims to deal with the problem of trajectory tracking control for the quadrotor under external environmental disturbance and variable payloads.

In the field of unmanned aerial vehicle (UAV) control, external environmental disturbance and internal variable payloads as two major interference factors lead to control performance degradation or even instability, thus a trajectory tracking controller which innovatively combines sliding mode control technology and model-free control technique is proposed. The proposed controller is constructed with a learning rate-based sliding mode controller and an ultra-local model. Based on the proposed controller, the nonlinear system model of variable load quadrotor is locally estimated and the system’s uncertainties and disturbances can be compensated.

The simulation and actual test results demonstrate the satisfactory control performance and the robustness of the proposed controller compared with the PID and Backstepping controller under external environmental disturbance and variable payloads. Moreover, the proposed controller solves the trajectory tracking control problem not only when payloads change at the center of gravity but also when the position of load variation deviates from the center of gravity.

In both military and civilian domains, the quadrotor may encounter such situations that the payloads change, such as transporting goods, aerial refueling and so on. As a large internal interference factor, variable load tends to lead to unstable control. The research results provide theoretical guidance and technical support for trajectory tracking control of quadrotor under variable payloads.

The proposed controller combines learning rate-based sliding mode controller and model-free control technique to achieve a more efficient and accurate trajectory control of the quadrotor when considering system uncertainties and the load variation that happens in the unknown location.

This study aims to optimize autonomous performance (i.e. both longitudinal and lateral) and endurance of the quadrotor type aerial vehicle simultaneously depending on the autopilot gain coefficients and battery weight.

Quadrotor design processes are critical to performance. Unmanned aerial vehicle durability is an important performance parameter. One of the factors affecting durability is the battery. Battery weight, energy capacity and discharge rate are important design parameters of the battery. In this study, proper autopilot gain coefficients and battery weight are obtained by using a stochastic optimization method named as simultaneous perturbation stochastic approximation (SPSA). Because there is no direct correlation between battery weight and battery energy density, artificial neural network (ANN) is benefited to obtain battery energy density corresponding to resulted battery weight found from SPSA algorithm. By using the SPSA algorithm optimum performance index is obtained, then obtained data is used for longitudinal and lateral autonomous flight simulations.

With SPSA, the best proportional integrator and derivative (PID) coefficients and battery weight, energy efficiency and endurance were obtained in case of morphing.

It takes a long time to find the most suitable battery values depending on quadrotor endurance. However, this situation can be overcome with the proposed SPSA.

It is very useful to determine quadrotor endurance, PID coefficients and morphing rate using the optimization method.

Determining quadrotor endurance, PID coefficients and morphing rate using the optimization method provides advantages in terms of time, cost and practicality.

The proposed method improves quadrotor endurance. In addition, with the SPSA optimization method and ANN, the parameters required for endurance will be obtained faster and more securely. In addition, the energy density according to the battery weight also contributes to the clean environment and energy efficiency.

The purpose of this paper is to design a hybrid robust tracking controller based on an improved radial basis function artificial neural network (IRBFANN) and a novel extended-state observer for a quadrotor system with various model and parametric uncertainties and external disturbances to enhance the resiliency of the control system.

An IRBFANN is introduced as an adaptive compensator tool for model and parametric uncertainties in the control algorithm of non-singular rapid terminal sliding-mode control (NRTSMC). An exact-time extended state observer (ETESO) augmented with NRTSMC is designed to estimate the unknown exogenous disturbances and ensure fast states convergence while overcoming the singularity issue. The novelty of this work lies in the online updating of weight parameters of the RBFANN algorithm by using a new idea of incorporating an exponential sliding-mode effect, which makes a remarkable effort to make the control protocol adaptive to uncertain model parameters. A comparison of the proposed scheme with other conventional schemes shows its much better performance in the presence of parametric uncertainties and exogenous disturbances.

The investigated control strategy presents a robust adaptive law based on IRBFANN with a fast convergence rate and improved estimation accuracy via a novel ETESO.

To enhance the safety level and ensure stable flight operations by the quadrotor in the presence of high-order complex disturbances and uncertain environments, it is imperative to devise a robust control law.

A new idea of incorporating an exponential sliding-mode effect instead of conventional approaches in the algorithm of the RBFANN is used, which makes the control law resistant to model and parametric uncertainties. The ETESO provides rapid and accurate disturbance estimation results and updates the control law to overcome the performance degradation caused by the disturbances. Simulation results depict the effectiveness of the proposed control strategy.

This paper aims to investigate the distributed formation control problem for a multi-quadrotor unmanned aerial vehicle system without linear velocity feedbacks.

A nonlinear controller is proposed based on the orthogonal group SE(3) to obviate singularities and ambiguities of the traditional parameterized attitude representations. A cascade structure is applied in the distributed controller design. The inner loop is responsible for attitude control, and the outer loop is responsible for translational dynamics. To ensure a linear-velocity-free characteristic, some auxiliary variables are introduced to construct virtual signals in distributed controller design. The stability analysis of the proposed distributed control method by the Lyapunov function is provided as well.

A group of four quadrotors with constant reference linear velocity and a group of six quadrotors with varying reference linear velocity are adopted to verify the effectiveness of the proposed strategy.

This is a new innovation for multi-robot formation control method to improve assembly automation.

The hybrid control system of the nonlinear PID (NLPID) controller and improved active disturbance rejection control (IADRC) are proposed for stabilization purposes for a 6-degree freedom (DoF) quadrotor system with the existence of exogenous disturbances and system uncertainties.

IADRC units are designed for the altitude and attitude systems, while NLPID controllers are designed for the x−y position system on the quadrotor nonlinear model. The proposed controlling scheme is implemented using MATLAB/Simulink environment and is compared with the traditional PID controller and NLPID controller.

Different tests have been done, such as step reference tracking, hovering mode, trajectory tracking, exogenous disturbances and system uncertainties. The simulation results showed the demonstrated performance and stability gained by using the proposed scheme as compared with the other two controllers, even when the system was exposed to different disturbances and uncertainties.

The study proposes an NLPID-IADRC scheme to stabilize the motion of the quadrotor system while tracking a specified trajectory in the presence of exogenous disturbances and parameter uncertainties. The proposed multi-objective Output Performance Index (OPI) was used to obtain the optimum integrated time of the absolute error for each subsystem, UAV quadrotor system energy consumption and for minimizing the chattering phenomenon by adding the integrated time absolute of the control signals.

The purpose of this paper is to introduce a low-cost quadrotor that can be used for educational purposes and investigate the applicability of a low-cost MEMS laser sensor for accurate altitude control.

A single printed circuit board is designed to form the structure of the quadrotor. A low-cost MEMS motion sensor, a microcontroller and four small motors are mounted on the board. A separate laser sensor module measures the altitude. A remote controller is designed to control the quadrotor’s motion. The remote controller communicates with the quadrotor via wireless connection. Roll and pitch attitude stabilization is achieved using the proportional and derivative control algorithm. The applicability of an MEMS laser sensor for altitude control is also studied.

The low-cost quadrotor works well even though its body structure is made using a printed circuit board. Low pass and Kalman filters work well for attitude estimation and control application. The laser sensor is very accurate and good for altitude feedback; however, it has a relatively short measurement range and its sampling rate is relatively slow, which limits its applications. The vertical velocity obtained by differentiating the laser altitude has delay and inhibits suitable damping. Using the vertical velocity obtained by integrating the vertical accelerometer’s output, the damping performance is improved.

Developing a low-cost quadrotor that can be used for educational purposes and successfully implementing altitude control using a laser sensor and accelerometer.

This study aims to develop a quadrotor with a robust control system against weight variations. A Proportional-Integral-Derivative (PID) controller based on Particle Swarm Optimization and Differential Evaluation to tune the parameters of PID has been implemented with real-time simulations of the quadrotor.

The optimization algorithms are combined with the PID control mechanism of the quadrotor to increase the performance of the trajectory tracking for a quadrotor. The dynamical model of the quadrotor is derived by using Newton-Euler equations.

In this study, the most efficient control parameters of the quadrotor are selected using evolutionary optimization algorithms in real-time simulations. The control parameters of PID directly affect the controller’s performance that position error and stability improved by tuning the parameters. Therefore, the optimization algorithms can be used to improve the trajectory tracking performance of the quadrotor.

The online optimization result showed that evolutionary algorithms improve the performance of the trajectory tracking of the quadrotor.

This study states the design of an optimized controller compared with manually tuned controller methods. Fitness functions are defined as a custom fitness function (overshoot, rise-time, settling-time and steady-state error), mean-square-error, root-mean-square-error and sum-square-error. In addition, all the simulations are performed based on a realistic simulation environment. Furthermore, the optimization process of the parameters is implemented in real-time that the proposed controller searches better parameters with real-time simulations and finds the optimal parameter online.

In the previous decade, unmanned aerial vehicles (UAVs) have turned into a subject of enthusiasm for some exploration associations. UAVs are discovering applications in different regions going from military applications to activity reconnaissance. The purpose of this paper is to overview a particular sort of UAV called quadrotor or quadcopter.

This paper includes the dynamic models of a quadrotor and the distinctive model-reliant and model-autonomous control systems and their correlation.

In the present time, focus has moved to outlining autonomous quadrotors. Ultimately, the paper examines the potential applications of quadrotors and their part in multi-operators frameworks.

This investigation deals with the review on various quadrotors, their applications and motion control strategies.