Herein, we investigate the robust formation control problem for a group of unmanned aerial vehicles (UAVs) with system uncertainty. A hierarchical formation control strategy is introduced to ensure the uniform ultimate boundedness of each UAV’s...
This paper presents a method for use in estimating the state of charge (SOC) of lithium-ion batteries which is based on an electrochemical impedance equivalent circuit model with a controlled source. Considering that the open-circuit voltage of a bat...
Quadrotor unmanned aerial vehicles (QUAVs) are widely recognized for their versatility and advantages across diverse applications. However, their inherent instability and underactuated dynamics pose significant challenges, particularly under external...
This article presents an adaptive neural network (ANN) control scheme based on a disturbance observer that can achieve trajectory tracking control of robotic manipulators under external disturbances and dynamic model uncertainties. Firstly, an ANN co...
Although there have been some severe nuclear accidents such as Three Mile Island (USA), Chernobyl (Ukraine) and Fukushima (Japan), nuclear fission energy is still a source of clean energy that can substitute for fossil fuels in a centralized way and...
A novel zeroing neural network control scheme based on an extended state observer is proposed for the trajectory tracking of a tracked mobile robot which is subject to unknown external disturbances and uncertainties. To estimate unknown lumped distur...
The microgrids operate in tie-up (TU) mode with the main grid normally, and operate in isolation (IN) mode without the main grid during faults. In a dynamic operational regime, protecting the microgrids is highly challenging. This article proposes a...
This article proposes an observer-based predefined-time robust formation controller for uncertain multi-UAV systems with external disturbances by integrating the sliding-mode technique with neural networks. The predefined-time strategy is developed t...
A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearitie...
Newton’s second law has been applied to create a dynamic model of the lateral motion of a supercavitating vehicle, assuming a stable cavity. However, some states cannot be measured, and there is uncertainty in the lateral model. Aiming to resol...
This paper addresses the attitude tracking control problem for laterally symmetric vehicles during the boost phase under aerodynamic parameter variations and high-altitude wind disturbances. A neural disturbance observer-based nonsingular predefined-...
The rehabilitation exoskeleton is an effective piece of equipment for stroke patients and the aged. However, this complex human–robot system incurs many problems, such as modeling uncertainties, unknown human–robot interaction, external d...
This study addresses the challenge of designing an event-triggered observer for neural network-enhanced sliding mode control in nonlinear Takagi–Sugeno fuzzy Markov jump systems, where premise variables are not directly measurable. Firstly, for...
Thiswork addresses the trajectory-tracking-control problem for a quadrotor unmanned aerial vehicle with external disturbances and parameter uncertainties. A novel adaptive-dynamic-programming-based robust control method is proposed to eliminate the e...
This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberge...
In this paper, a novel approach involving a fractional recurrent neural network (RNN) is proposed to achieve the observer-based synchronization of a cancer cell model. According to the properties of recurrent neural networks, our proposed framework s...
In this paper, we explore the problem of smooth braking at preset points in autonomous vehicles using model predictive control (MPC) with a receding horizon extended state observer (RHESO) and a neural network (NN). An NN-based modeling method is pro...
The accurate detection and identification of collision states in industrial robot environments is a critically important and challenging task. Deep learning-based methods have been widely applied to collision detection; however, these methods primari...
Precise speed estimation of sensorless induction motor (SIM) drives remains a significant challenge, particularly at zero and very low speeds. This paper proposes a mathematically modeled and enhanced stator current-based Model Reference Adaptive Sys...
Low-voltage direct current (DC) microgrid based on distributed generation (DG), the problems of load mutation affecting the DC bus under island mode, and the security problems that may arise when the DC microgrid is switched from island mode to grid-...
This paper studies spacecraft control under communication congestion, multi-source uncertainties, and input constraints. To reduce communication load, a static event-triggered mechanism is used so that transmissions occur only when necessary. Unknown...
Piezoelectric actuators (PEAs) have the benefits of a high-resolution and high-frequency response and are widely applied in the field of micro-/nano-high-precision positioning. However, PEAs undergo nonlinear hysteresis between input voltage and outp...
Total Electron Content (TEC) is a fundamental parameter characterizing the electron density distribution in the ionosphere. Traditional global TEC modeling approaches predominantly rely on mathematical methods (such as spherical harmonic function fit...
The captured energy of a wind turbine (WT) can be converted into electricity by a generator. Therefore, to improve the efficiency of this system, both the structures of WTs and generators should be considered for control. But the present challenge is...
Fault diagnosis is crucial for ensuring the reliability and safety of wind energy conversion systems (WECSs). However, existing methods are often specific to components or specific types of wind turbines and face challenges, such as difficulty in thr...
This paper summarizes a robust controller based on the fact that, in the operation of a permanent magnet synchronous motor (PMSM), a number of disturbance factors naturally occur, among which both changes in internal parameters (e.g., stator resistan...
An innovative cascade predictor is presented in this study to forecast the state of recurrent neural networks (RNNs) with delayed output. This cascade predictor is a chain-structured observer, as opposed to the conventional single observer, and is ma...
This research proposes a fractional-order adaptive neural control scheme using an optimized backstepping (OB) approach to address strict-feedback nonlinear systems with uncertain control directions and predefined performance requirements. The OB fram...
Near-pace hypersonic flight has great potential in civil and military use due to its high speed and low cost. To optimize the design and improve the robustness, this paper focuses on the integrated guidance and control (IGC) design with nonlinear act...
The health monitoring of CRF (circulation water) pumps is essential for prognostics and management in nuclear power plants. However, the operational status of CRF pumps can vary due to environmental factors and human intervention, and the interrelati...
Pneumatic actuator is one of the key technologies in the field of active suspension due to its low cost, cleanliness, and high power-to-weight ratio characteristics. However, the dynamic models and control strategies of the pneumatic suspension have...
For achieving high-performance control for a particleboard glue mixing and dosing control system, which is a time-delay system in low frequency working conditions, an improved active disturbance rejection controller is proposed. In order to reduce ov...
Due to the hostile marine environment, there will inevitably be unpredictable factors during the operation of unmanned underwater vehicles, including changes in ocean currents, hull dimensions, and velocity measurement uncertainties. An improved fini...
In this article, we define the outlier detection task and use it to compare neural-based word embeddings with transparent count-based distributional representations. Using the English Wikipedia as a text source to train the models, we observed that e...
Deep learning architectures have received much attention in recent years demonstrating state-of-the-art performance in several segmentation, classification and other computer vision tasks. Most of these deep networks are based on either convolutional...
Breast cancer is the most prevalent neoplasia among women, with early and accurate diagnosis critical for effective treatment. In clinical practice, however, the subjective nature of histological grading of infiltrating ductal adenocarcinoma of the b...
This paper presents the design of an event-triggered state estimator for neural sliding mode control (SMC) in networked nonlinear Markov jump systems (MJSs) with incomplete mode information. To improve communication efficiency, a simulated annealing-...
A dual-loop fault-tolerant control scheme is investigated for UAV attitude control systems subject to actuator faults, input saturation, and external disturbances in this paper. In the outer loop of attitude angles, a nonlinear dynamic inversion cont...
This paper presents a unified framework for reliable motion control of permanent magnet linear motors (PMLMs) by integrating fault detection (FD) and fault-tolerant control (FTC). The framework combines a brain emotional learning-based intelligent co...
Weather is affected by a complex interplay of factors, including topography, location, and time. For the prediction of temperature in Korea, it is necessary to use data from multiple regions. To this end, we investigate the use of deep neural-network...
Sparse synthetic aperture radar (SAR) imaging has demonstrated excellent potential in image quality improvement and data compression. However, conventional observation matrix-based methods suffer from high computational overhead, which is hard to use...
An unknown nonlinear disturbance seriously affects the trajectory tracking of autonomous underwater vehicles (AUVs). Thus, it is critical to eliminate the influence of such disturbances on AUVs. To address this problem, this paper proposes a double-l...
In this work, the practical prescribed performance tracking issue for a class of fractional-order nonlinear multiple-input multiple-output (MIMO) systems with asymmetric full-state constraints and unmeasurable system states is investigated. A neural...
Aircraft wake vortices are serious threats to aviation safety. The Pulsed Coherent Doppler Lidar (PCDL) has been widely used in the observation of aircraft wake vortices due to its advantages of high spatial-temporal resolution and high precision. Ho...
This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with an unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constraine...
For ships on voyage, using satellite remote sensing observations is an effective way to access ocean temperature. However, satellite remote sensing observations can only provide the surface information. Additionally, this information obtained from sa...
In the present study, the effects of using a corrugated porous layer on the forced convection of a hybrid nanofluid flow over a 3D backward facing step are analyzed under the coupled effects of magnetic field and surface rotation. The thermal analysi...
For the numerical forecasting of ocean temperature, the effective fusion of observations and the initial field under the conditions of limited observations has always been a significant problem. Traditional data assimilation methods cannot make full...
This paper presents the study of integrating a deep motion model into simple online and real-time tracking for video multi-object tracking. The tracking-by-detection paradigm faces significant challenges in handling nonlinear motion and occlusions. A...
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