Article
Automation & Control Systems
Wentao Liu, Tong Zhao
Summary: This paper introduces an ADRC scheme using RBF neural networks for adaptive control of non-affine nonlinear systems. The dual-channel composite controller combines adaptive neural networks with ADRC design techniques, showing effectiveness in experiments.
Article
Computer Science, Information Systems
P. Parsa, M-R Akbarzadeh-T, F. Baghbani
Summary: This study introduces a command-filtered backstepping H1 robust adaptive emotional controller for strict-feedback nonlinear systems with mismatched uncertainties. The controller utilizes command filters and compensating filters to handle matched/mismatched uncertainties and disturbances, requiring only the known and continuous reference signal and its first derivative.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Kexin Ding, Qiang Chen, Yurong Nan, Xiaoye Luo
Summary: This paper presents an adaptive fixed-time neural control scheme for a class of nonlinear uncertain systems with full-state constraints. A novel asymmetric hyperbolic barrier Lyapunov function (AHBLF) is introduced to handle the time-varying constraints of all the system states. An adaptive controller is designed to ensure that the tracking errors converge to the equilibrium point within a fixed time, while the system states remain within predefined time-varying boundaries. The proposed control scheme avoids the singularity problem and does not require prior knowledge of the gain function bounds.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Ying Zhao, Peter Xiaoping Liu, Huanqing Wang
Summary: This study investigates the time-constrained positional synchronization control problem for a class of bilateral teleoperation systems and develops a novel fixed-time event-triggered control scheme. Unlike existing methods, the controller is triggered in a nonperiodic manner, significantly reducing the triggering frequency of control devices. Furthermore, the control settling time is considered by introducing a fixed-time stability theorem. Theoretical analysis and a simulation example confirm that the proposed control method can remarkably reduce the amount of control signals transmitted between the master and slave while ensuring the system output tracking error converges to a small neighborhood close to zero within a fixed-time frame.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2022)
Article
Automation & Control Systems
Lei Ma, Lei Liu
Summary: This paper presents an adaptive neural network constraint control method for uncertain nonlinear nonstrict feedback systems with state constraints, which successfully eliminates certain restrictive assumptions from previous studies, solves the algebraic loop problem based on the approximation structure using radial basis function (RBF) NNs, and achieves full state constraint satisfactions by employing barrier Lyapunov functions.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Kaixin Lu, Zhi Liu, Haoyong Yu, C. L. Philip Chen, Yun Zhang
Summary: This article proposes a decentralized adaptive neural inverse approach to address the complexity and time-consuming nature of solving Hamilton-Jacobi-Bellman (HJB) equations in decentralized optimal control of continuous-time nonlinear interconnected systems. By introducing a new criterion of inverse optimal practical stabilization and utilizing adaptive neural strategies, a decentralized inverse optimal controller is designed, demonstrating bounded closed-loop signals and achieving the goal of inverse optimality.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Mechanical
Jianfeng Wang, Ping Zhang, Yan Wang, Zhicheng Ji
Summary: This paper investigates the problem of adaptive optimal tracking control for full-state constrained strict-feedback nonlinear systems with input delay. A novel control approach is developed by combining the backstepping design technique and adaptive dynamic programming (ADP) theory. The approach utilizes Pade approximation to handle input delay and barrier Lyapunov functions for state constraints. Neural networks are employed to approximate unknown functions. An adaptive backstepping feedforward controller is developed to convert the tracking task into an equivalent regulation problem. A critic network is constructed within the ADP framework to obtain the optimal control. The resulting controller consists of feedforward and feedback parts, while ensuring that all signals are uniformly ultimately bounded in the closed-loop system.
NONLINEAR DYNAMICS
(2023)
Article
Computer Science, Artificial Intelligence
Lei Liu, Wei Zhao, Yan-Jun Liu, Shaocheng Tong, Yue-Ying Wang
Summary: This article proposes an adaptive finite-time neural control method which successfully solves multiple objective constraints, finite-time stability, singularity problem by introducing a new Lyapunov function and using a neural network to approximate unknown functions, achieving good tracking effects, and not violating constraint boundaries.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Engineering, Mechanical
Hai-Peng Ren, Shan-Shan Jiao, Jie Li, Yi Deng
Summary: Efforts in high performance tracking control of pneumatic position servo systems have achieved considerable results, but current methods often do not consider state constraints. This paper aims to improve tracking accuracy by employing RBFNN for unknown models, Nussbaum function for unknown control directions, and BLF for stability while considering state constraints. Experimental results demonstrate the effectiveness and superiority of the proposed method.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Computer Science, Artificial Intelligence
Sihui Zhou, Shuai Sui, Shaocheng Tong
Summary: This paper investigates an adaptive neural network (NN) optimal control problem for a permanent magnet synchronous motor (PMSM) system. The proposed control strategy using barrier performance index functions and barrier Lyapunov functions ensures the stability of the closed-loop system and guarantees the state variables of the PMSM are within given bounds while minimizing the performance index functions. The effectiveness of the developed NN adaptive optimal controller is verified through computer simulation results.
Article
Computer Science, Artificial Intelligence
Yu Liu, Xiongbin Chen, Yilin Wu, He Cai, Hiroshi Yokoi
Summary: This article focuses on the vibration reducing and angle tracking problems of a flexible unmanned spacecraft system subject to input nonlinearity, asymmetric output constraint, and system parameter uncertainties. A boundary control scheme is designed using the backstepping technique, with a modified asymmetric barrier Lyapunov function to ensure the output constraint is never transgressed. Neural networks are used to handle system parameter uncertainties and compensate for input nonlinearity, proving the stability of the closed-loop system based on Lyapunov analysis.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhiyong Zhou, Dongbing Tong, Qiaoyu Chen, Wuneng Zhou, Yuhua Xu
Summary: This paper discusses the use of radial basis function-neural networks for approximation in nonlinear systems and dynamic surface control method to address complexity issues, ensuring global asymptotic stability through Lyapunov stability theory. The effectiveness of the proposed control technique is validated through simulation examples.
Article
Engineering, Mechanical
Gang Luo, Bingxin Ma, Yongfu Wang
Summary: An observer-based adaptive neural network controller is developed for the Steer-by-Wire (SbW) system of automated vehicles with uncertain nonlinearity and unmeasured state. The controller effectively improves steering precision by estimating the angular velocity of the front wheels and using a radial basis function (RBF) neural network to model uncertain nonlinearity.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Chengjie Huang, Zhi Liu, C. L. Philip Chen, Yun Zhang
Summary: In this article, the problem of adaptive fixed-time tracking control for multiagent systems (MASs) with mismatched uncertainty is considered. A new adaptive consensus control criterion is proposed, which includes the design of Lyapunov functions and tuning functions. The use of radial basis function neural networks and direct adaptive strategy improves the stability and performance of the MASs.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Yi Yang, Haiyan H. Zhang
Summary: This paper presents an original radial basis function neural network-based adaptive fractional-order backstepping controller for reliable quadrotor operations in the presence of uncertain modeling parameters and unknown time-delayed inputs. The proposed controller eliminates the nonlinearity of time-delayed inputs by introducing an augmented state variable via Pade's approximation method. It ensures the semi-globally uniformly ultimately boundedness of all state variables and estimation error of uncertain parameters and demonstrates superior tracking accuracy and robustness compared to previous controllers.
FRACTAL AND FRACTIONAL
(2023)
Article
Chemistry, Multidisciplinary
Donglin Zhao, Jie Liang, Jun Li, Longcheng Zhang, Kai Dong, Luchao Yue, Yongsong Luo, Yuchun Ren, Qian Liu, Mohamed S. Hamdy, Quan Li, Qingquan Kong, Xuping Sun
Summary: This study reports that a TiO2-x nanobelt array with oxygen vacancies can convert nitrite into ammonia with high electrocatalytic efficiency and yield in alkaline solution.
CHEMICAL COMMUNICATIONS
(2022)
Article
Physics, Condensed Matter
Khadijah S. Al-Namshah, Mohd Shkir, Fatma A. Ibrahim, Mohamed S. Hamdy
Summary: In this study, pure ZnO and Co doped ZnO nanoparticles were successfully synthesized using flash combustion synthesis technique, and their properties were analyzed using various characterization techniques. The results showed that the Co doping enhanced the photocatalytic activity and affected the band gap and absorption spectrum of ZnO. The best performing sample was found to be 5 wt% Co doped ZnO with a rate constant 2.6 times higher than that of bare ZnO in the decolourization reaction.
PHYSICA B-CONDENSED MATTER
(2022)
Article
Chemistry, Inorganic & Nuclear
Jie Liang, Wen-Feng Hu, Bingyi Song, Ting Mou, Longcheng Zhang, Yongsong Luo, Qian Liu, Abdulmohsen Ali Alshehri, Mohamed S. Hamdy, Li-Ming Yang, Xuping Sun
Summary: The ever-increasing anthropic NO emission has caused severe environmental issues. Electrochemical reduction of NO has emerged as a promising approach for sustainable NO abatement and NH3 synthesis, but requires highly active and selective electrocatalysts. In this study, a CoP nanowire array on Ti mesh was used as an efficient catalyst for converting NO to NH3. This catalyst demonstrated excellent activity, selectivity, durability, and was also used as a cathode catalyst for a Zn-NO battery.
INORGANIC CHEMISTRY FRONTIERS
(2022)
Article
Oncology
Mohamed Hamdy, Amr Shafik, Emad Shash, Khaled Kamal, Basel Refky
INTERNATIONAL JOURNAL OF GYNECOLOGICAL CANCER
(2022)
Article
Biochemical Research Methods
Mohamed M. A. Hamdy, Mohamed A. Korany, Shaza A. Ebied, Rim S. Haggag
Summary: This study analyzed binary mixtures of novel oral anticoagulants and lipid lowering statins using HPLC-DAD method. The method was suitable for quantitative assay of the mixtures in tablets and human plasma, and could separate possible degradation products. This analysis is important for clinical monitoring of cardiovascular patients.
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES
(2022)
Article
Chemistry, Physical
Peipei Wei, Jie Liang, Qian Liu, Lisi Xie, Xin Tong, Yuchun Ren, Tingshuai Li, Yongsong Luo, Na Li, Bo Tang, Abdullah M. Asiri, Mohamed S. Hamdy, Qingquan Kong, Zhiming Wang, Xuping Sun
Summary: In this study, Fe-doped Co3O4 nanoarray is reported to efficiently catalyze NO3RR for NH3 production in neutral conditions, achieving high yield and Faradaic efficiency.
JOURNAL OF COLLOID AND INTERFACE SCIENCE
(2022)
Correction
Computer Science, Artificial Intelligence
Sameh Abd-Elhaleem, Mohamed Soliman, Mohamed Hamdy
Article
Computer Science, Artificial Intelligence
Sameh Abd-Elhaleem, Mohamed Soliman, Mohamed Hamdy
Summary: This paper considers the problems of periodic signal tracking and disturbance rejection for a class of time-varying delay nonlinear systems with unknown exogenous disturbances under limited communication resources. The Takagi-Sugeno fuzzy model is used to approximate the nonlinear system. The developed scheme achieves periodic reference tracking and improves the performance of periodic and aperiodic unknown disturbances rejection effectively. A fuzzy periodic event-triggered feedback observer is proposed to reduce computational burden, energy consumption, and save communication resources. The overall system consists of the repetitive controller, equivalent-input-disturbance estimator, and fuzzy periodic event-triggered feedback observer based on a Takagi-Sugeno fuzzy model. Sufficient conditions for the asymptotic stability of the overall system subjected to unknown disturbances are derived using stability theory and linear matrix inequalities. Simulation results demonstrate the effectiveness and feasibility of the proposed scheme.
Correction
Computer Science, Artificial Intelligence
Salah Helmy, Mohamed Magdy, Mohamed Hamdy
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Chemistry, Physical
Asif Hayat, Muhammad Sohail, Mohamed S. Hamdy, T. A. Taha, Huda Salem AlSalem, Asma M. Alenad, Mohammed A. Amin, Rahim Shah, Arkom Palamanit, Javid Khan, W. Nawawi, Sunil Kumar Baburao Mane
Summary: This article summarizes the research progress and applications of semiconductor-based boron nitride (BN) and its composites. BN has multiple advantages, making it potentially useful in energy, environmental, and pharmaceutical fields. The various synthesis routes for BN and its composites are discussed, along with their applications in photocatalysis, drug delivery, and sensors, as well as the challenges faced.
SURFACES AND INTERFACES
(2022)
Article
Geosciences, Multidisciplinary
Mohamed M. Hamdy, El Saeed R. Lasheen, Wael Abdelwahab
Summary: Dike-like variable listwaenites with significant Au have been exposed in serpentinite fault zones in Um Khasila-Um Huweitat (Kh-H) and Malo Grim (MG) areas of Egypt's Eastern Desert. The different types and formation processes of the serpentinites in these areas have resulted in variations in the elemental content of the mineralized veins. The Kh-H serpentinites have been influenced by fluids from continental crust, leading to the formation of K2O-rich carbonate listwaenite, while the MG serpentinites have primarily been affected by the carbonation process, resulting in silica-rich carbonate listwaenite.
JOURNAL OF AFRICAN EARTH SCIENCES
(2022)
Article
Automation & Control Systems
Sameh Abd-Elhaleem, Mohamed Soliman, Mohamed Hamdy
Summary: This article addresses the problems of disturbance rejection and periodic signal tracking for a certain class of time-varying delay nonlinear systems subjected to unknown exogenous disturbances. A Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinearity of the system. The proposed modified repetitive controller (MRC) and adaptive periodic event triggered mechanism based fuzzy state observer (APETM-FSO) improve the performance of disturbances rejection and achieve good tracking performance for periodic references. Sufficient conditions based on the Lyapunov-Krasovskii functional stability theory and linear matrix inequalities (LMIs) are derived to achieve the asymptotic stability of the overall system. Simulation results are presented to demonstrate the effectiveness and feasibility of the proposed scheme.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Mohamed Hamdy, Amal Ibrahim, Belal Abozalam, Salah Helmy
Summary: Maximum power point tracking (MPPT) is a technique used in photovoltaic (PV) arrays to optimize their energy generation in varying weather conditions. The article proposes a new fuzzy logic algorithm, Type-3 fuzzy logic (T3FL), which improves tracking efficiency and speed by better dealing with uncertainties. Simulation and experimental studies demonstrate the effectiveness of the T3FL algorithm.
ELECTRIC POWER COMPONENTS AND SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Quanying Chen, Jie Liang, Qin Liu, Kai Dong, Luchao Yue, Peipei Wei, Yongsong Luo, Qian Liu, Na Li, Bo Tang, Abdulmohsen Ali Alshehri, Mohamed S. Hamdy, Zhenju Jiang, Xuping Sun
Summary: In this study, Co nanoparticle-decorated pomelo-peel-derived carbon is demonstrated as an efficient electrocatalyst for nitrate reduction to ammonia, achieving high faradaic efficiency and yield.
CHEMICAL COMMUNICATIONS
(2022)
