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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.

The purpose of this paper is to develop a novel active disturbance rejection attitude controller for quadrotors and propose a controller parameters identification approach to obtain better control results.

Aiming at the problem that quadrotor is susceptible to disturbance in outdoor flight, the improved active disturbance rejection control (IADRC) is applied to design attitude controller. To overcome the difficulty that adjusting the parameters of IADRC controller manually is complex, paired coevolution pigeon-inspired optimization (PCPIO) algorithm is used to optimize the control parameters.

The IADRC, where nonlinear state error feedback control law is replaced by non-singular fast terminal sliding mode control law and a third-order tracking differentiator is designed for second derivative of the state, has higher control accuracy and better robustness than ADRC. The improved PIO algorithm based on evolutionary mechanism, named PCPIO, is proposed. The optimal parameters of ADRC controller are found by PCPIO with the optimization criterion of integral of time-weighted absolute value of the error. The effectiveness of the proposed method is verified by a series of simulation experiments.

IADRC can improve the accuracy of attitude control of quadrotor and resist external interference more effectively. The proposed PCPIO algorithm can be easily applied to practice and can help the design of the quadrotor control system.

An improved active disturbance rejection controller is designed for quadrotor attitude control, and a hybrid model of PIO and evolution mechanism is proposed for parameters identification of the controller.

Oscillations and related stability problems of synchronous generators are harmful and can lead to power outage. Studies have shown that currently available commercial applications of power system stabilizers (PSSs) do not ensure damping of modern generators operating in contemporary power systems at peak performances. The purpose of this paper is to contribute to development of the new PSS, which would replace currently used linear stabilizers.

A synthesis of theoretical research, numerical simulations and laboratory experiments was the basic framework.

Within a problem analysis, it was empirically confirmed that the currently used PSSs are not up to the needs of the present power systems. Based on an analysis of the contemporary solutions, it was found out that the most appropriate solutions are adaptive control and robust control. In this paper, the robust sliding mode theory was implemented for the PSS design.

The most notable restriction of rapid transfer of scientific solutions into a practice represents limited testing of proposed solutions on synchronous generators in power plants.

The new PSS which would replace currently used conventional stabilizers will have an exceptional value for all producers of the excitation systems.

The originality of the paper represents the development of the new robust sliding mode PSS and qualitative assessment of the developed stabilizer with two competitive stabilizers, i.e. the conventional linear- and advanced direct adaptive-PSS.

This paper aims to investigate the problem of attitude control for a horizontal takeoff and horizontal landing reusable launch vehicle.

In this paper, a predefined-time attitude tracking controller is presented for a horizontal takeoff and horizontal landing reusable launch vehicle (HTHLRLV). Firstly, the attitude tracking error dynamics model of the HTHLRLV is developed. Subsequently, a novel sliding mode surface is designed with predefined-time stability. Furthermore, by using the proposed sliding mode surface, a predefined-time controller is derived. To compensate the external disturbances or model uncertainties, a fixed-time disturbance observer is developed, and its convergence time can be defined as a prior control parameter. Finally, the stability of the proposed sliding mode surface and the controller can be proved by the Lyapunov theory.

In contrast to other fixed-time methods, this controller only requires three control parameters, and the convergence time can be predefined instead of being estimated. The simulation results also demonstrate the effectiveness of the proposed controller.

A novel predefined-time attitude tracking controller is developed based on the predefined-time sliding mode surface (SMS) and fixed-time disturbance observer (FxTDO). The convergence time of the system can be selected as a prior control parameter for SMS and FxTDO.

This paper aims to present a control strategy that eliminates the longitudinal and lateral drifting movements of the coaxial ducted fan unmanned helicopter (UH) during autonomous take-off and landing and reduce the coupling characteristics between channels of the coaxial UH for its special model structure.

Unidirectional auxiliary surfaces (UAS) for terminal sliding mode controller (TSMC) are designed for the flight control system of the coaxial UH, and a hierarchical flight control strategy is proposed to improve the decoupling ability of the coaxial UH.

It is demonstrated that the proposed height control strategy can solve the longitudinal and lateral movements during autonomous take-off and landing phase. The proposed hierarchical controller can decouple vertical and heading coupling problem which exists in coaxial UH. Furthermore, the confronted UAS-TSMC method can guarantee finite-time convergence and meet the quick flight trim requirements during take-off and landing.

The designed flight control strategy has not implemented in real flight test yet, as all the tests are conducted in the numerical simulation and simulation with a hardware-in-the-loop (HIL) platform.

The designed flight control strategy can solve the common problem of coupling characteristics between channels for coaxial UH, and it has important theoretical basis and reference value for engineering application; the control strategy can meet the demands of engineering practice.

In consideration of the TSMC approach, which can increase the convergence speed of the system state effectively, and the high level of response speed requirements to UH flight trim, the UAS-TSMC method is first applied to the coaxial ducted fan UH flight control. The proposed control strategy is implemented on the UH flight control system, and the HIL simulation clearly demonstrates that a much better performance could be achieved.

The purpose of this paper is to solve the challenging problem of automatic carrier landing with the presence of environmental disturbances. Therefore, a global fast terminal sliding mode control (GFTSMC) method is proposed for automatic carrier landing system (ACLS) to achieve safe carrier landing control.

First, the framework of ACLS is established, which includes flight glide path model, guidance model, approach power compensation system and flight controller model. Subsequently, the carrier deck motion model and carrier air-wake model are presented to simulate the environmental disturbances. Then, the detailed design steps of GFTSMC are provided. The stability analysis of the controller is proved by Lyapunov theorems and LaSalle’s invariance principle. Furthermore, the arrival time analysis is carried out, which proves the controller has fixed time convergence ability.

The numerical simulations are conducted. The simulation results reveal that the proposed method can guarantee a finite convergence time and safe carrier landing under various conditions. And the superiority of the proposed method is further demonstrated by comparative simulations and Monte Carlo tests.

The GFTSMC method proposed in this paper can achieve precise and safe carrier landing with environmental disturbances, which has important referential significance to the improvement of ACLS controller designs.

This paper aims to propose a novel control scheme and offer a control parameter optimizer to achieve better automatic carrier landing. Carrier landing is a challenging work because of the severe sea conditions, high demand for accuracy and non-linearity and maneuvering coupling of the aircraft. Consequently, the automatic carrier landing system raises the need for a control scheme that combines high robustness, rapidity and accuracy. In addition, to exploit the capability of the proposed control scheme and alleviate the difficulty of manual parameter tuning, a control parameter optimizer is constructed.

A novel reference model is constructed by considering the desired state and the actual state as constrained generalized relative motion, which works as a virtual terminal spring-damper system. An improved particle swarm optimization algorithm with dynamic boundary adjustment and Pareto set analysis is introduced to optimize the control parameters.

The control parameter optimizer makes it efficient and effective to obtain well-tuned control parameters. Furthermore, the proposed control scheme with the optimized parameters can achieve safe carrier landings under various severe sea conditions.

The proposed control scheme shows stronger robustness, accuracy and rapidity than sliding-mode control and Proportion-integration-differentiation (PID). Also, the small number and efficiency of control parameters make this paper realize the first simultaneous optimization of all control parameters in the field of flight control.

This paper aims to design an adaptive nonlinear strategy capable of timely detection and reconstruction of faults in the attitude’s sensors of an autonomous aerial vehicle with greater accuracy concerning other conventional approaches in the literature.

The proposed scheme integrates a baseline nonlinear controller with an improved radial basis function neural network (IRBFNN) to detect different kinds of anomalies and failures that may occur in the attitude’s sensors of an autonomous aerial vehicle. An integral sliding mode concept is used as auto-tune weight update law in the IRBFNN instead of conventional weight update laws to optimize its learning capability without computational complexities. The simulations results and stability analysis validate the promising contributions of the suggested methodology over the other conventional approaches.

The performance of the proposed control algorithm is compared with the conventional radial basis function neural network (RBFNN), multi-layer perceptron neural network (MLPNN) and high gain observer (HGO) for a quadrotor vehicle suffering from various kinds of faults, e.g. abrupt, incipient and intermittent. From the simulation results obtained, it is found that the proposed algorithm’s performance in faults detection and estimation is relatively better than the rest of the methodologies.

For the improvement in the stability and safety of an autonomous aerial vehicle during flight operations, quick identification and reconstruction of attitude’s sensor faults and failures always play a crucial role. Efficient fault detection and estimation scheme are considered indispensable for an error-free and safe flight mission of an autonomous aerial vehicle.

The proposed scheme introduces RBFNN techniques to detect and estimate the quadrotor attitude’s sensor faults and failures efficiently. An integral sliding mode effect is used as the network’s backpropagation law to automatically modify its learning parameters accordingly, thereby speeding up the learning capabilities as compared to the conventional neural network backpropagation laws. Compared with the other investigated techniques, the proposed strategy achieve remarkable results in the detection and estimation of various faults.

The purpose of this paper is to design a controller for a quadrotor only by using input–output data without a need for the system model.

Tracking control for the quadrotor is considered by using unfalsified control, which is one of the most recent strategies of robust adaptive control. The main assumption in unfalsified control design is that there is no access to the system model. Also, ideal path tracking and controlling the quadrotor are been paid attention to in the presence of external disturbances and uncertainties. First, unfalsified control method is introduced which is a data-driven and model-free approach in the field of adaptive control. Next, model of the quadrotor and unfalsified control design for the quadrotor are presented. Second, design of a control bank consisting of four proportional integral derivative controllers and a sliding mode controller is carried out.

A particular innovation on an unfalsified control algorithm in this paper is use of a generalized cost function in the hysteresis switching algorithm to find the best controller.

Finally, the performance and robustness of the designed controllers are investigated by simulation studies in various operating conditions including reference trajectory changes, facing to wind disturbance, uncertainty of the system and changes in payload, which show acceptable performances.

In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression.

This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance.

It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect.

The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved.

In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.