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Observer-based multivariable fixed-time formation control of mobile robots

Journal of Systems engineering and Electronics 2020年第2期31卷 403-414页

作者： LI Yandong ZHU Ling and GUO Yuan College of Computer and Control Engineering Qiqihar UniversityQiqihar 161006China School of Mechanical and Electronic Engineering Qiqihar UniversityQiqihar 161006China

This paper proposes a multivariable fixed-time leaderfollower formation control method for a group of nonholonomic mobile robots, which has the ability to estimate multiple uncertainties. Firstly, based on the state space model of the leader-follower formation, a multivariable fixed-time formation kinematics controller is designed. Secondly, to overcome uncertainties existing in the nonholonomic mobile robot system, such as load change,friction, external disturbance, a multivariable fixed-time torque controller based on the fixed-time disturbance observer at the dynamic level is designed. The designed torque controller is cascaded with the formation controller and finally realizes accurate estimation of the uncertain part of the system, the follower tracking of reference velocity and the desired formation of the leader and the follower in a fixed-time. The fixed-time upper bound is completely determined by the controller parameters, which is independent of the initial state of the system. The multivariable fixed-time control theory and the Lyapunov method are adopted to ensure the system ***, the effectiveness of the proposed algorithm is verified by the experimental simulation.

关键词： multivariable fixed-time control formation control uncertainty fixed time observer nonholonomic mobile robot

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Joint Optimization of Power Allocation and Beamforming for UAV-RIS Communication System

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IEEE Wireless Communications Letters 2025年

作者： Guo, Xinying Liu, Longfei Zhang, Jiankang Chen, Sheng Ministry of Education Key Laboratory of Grain Information Processing and Control Henan University of Technology China Henan University of Technology College of Information Science and Engineering Zhengzhou450001 China Bournemouth University Department of Computing and Informatics BH12 5BB United Kingdom University of Southampton School of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

This paper considers the communication system assisted by a fixed-trajectory unmanned aerial vehicle (UAV), which is equipped with a reconfigurable intelligent surface (RIS). For this UAV-RIS assisted system, we jointly optimize the power allocation and active beamforming at the base station (BS) and the passive beamforming at the RIS, by a novel phase block coordinate descent algorithm framework aimed at maximizing the system sum-rate. Specifically, the joint optimization problem is decomposed into two phases, and we propose two optimization algorithms: one for BS power allocation using fractional programming (FP) and the other for jointly optimizing active and passive beamforming using FP-manifold, which alternately optimize two phases. Simulation results not only highlight the rapid convergence and evident superiority of our proposed framework but also reveal that the optimal UAV-RIS placement is related to the flight height. © 2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A framework for load frequency regulation in multi-area grid-connected hybrid power systems with plug-in electric vehicles

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Renewable Energy Focus 2025年 54卷

作者： Gulzar, Muhammad Majid Jameel, Ahlam Habib, Salman Arishi, Ali Irfan, Rasmia Ahmad, Hasnain Tehreem, Huma Department of Control & Instrumentation Engineering King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Department of Electrical Engineering Lahore College for Women University Lahore54000 Pakistan King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia Department of Industrial Engineering King Khalid University Abha61421 Saudi Arabia Institute of Electrical Electronics and Computer Engineering University of the Punjab Lahore54000 Pakistan Islamabad45650 Pakistan School of Computing Engineering & Digital Technologies Teesside University Middlesbrough Campus TS1 3BX United Kingdom

Due to technological advancements, the rapid expansion of renewable energy in the power sector has led to challenges with operation, security, and management. Reduced grid inertia necessitates maintaining normal operating frequency and lowering tie-line power changes to assure stability and reliability. In this article, a framework for load frequency controller (LFC) that is based on the combinations of traditional controllers is proposed. In this study, the filtered derivative proportional controller cascaded with β proportional integral, abbreviated as PDF+(β+PI), is suggested for LFC applications. In addition, the optimization of the proposed controller parameters for two-area power grids is tuned using the grasshopper optimization algorithm (GOA). The contribution of aggregated model for electric vehicles (EVs) is also taken into consideration. The performance of the proposed controller is evaluated with the effectiveness of other controllers like cascaded proportional integral and derivative (PI-PD), 1 plus proportional integral derivative (1+PID), 1 plus proportional integral (1+PI), and fractional order proportional integral derivative (FOPID). The proposed GOA optimizer tuned PDF+(β+PI) controller is tested for reliability against variations in load, penetration of renewable energy sources, and parametric uncertainties of the grid for the time integral absolute error (ITAE) objective function. By employing the proposed controller, the system achieves rapid and efficient minimization of the objective function. Thus, the controller is highly suitable for applications requiring quick response and precise performance. © 2025 Elsevier Ltd

关键词： Two term control systems

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Solving type-2 fuzzy relation equations via semi-tensor product of matrices

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control Theory and Technology 2014年第2期12卷 173-186页

作者： Yongyi YAN Zengqiang CHEN Zhongxin LIU College of Computer and Control Engineering Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University

The problem of solving type-2 fuzzy relation equations is investigated. In order to apply semi-tensor product of matrices, a new matrix analysis method and tool, to solve type-2 fuzzy relation equations, a type-2 fuzzy relation is decomposed into two parts as principal sub-matrices and secondary sub-matrices; an r-ary symmetrical-valued type-2 fuzzy relation model and its corresponding symmetrical-valued type-2 fuzzy relation equation model are established. Then, two algorithms are developed for solving type-2 fuzzy relation equations, one of which gives a theoretical description for general type-2 fuzzy relation equations; the other one can find all the solutions to the symmetrical-valued ones. The results can improve designing type-2 fuzzy controllers, because it provides knowledge to search the optimal solutions or to find the reason if there is no solution. Finally some numerical examples verify the correctness of the results/algorithms.

关键词： Fuzzy control system Type-2 fuzzy logic system Type-2 fuzzy relation Type-2 fuzzy relation equation Semi- tensor product of matrices

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TSGN: Transaction Subgraph Networks Assisting Phishing Detection in Ethereum

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Wang, Jinhuan Chen, Pengtao Xu, Xinyao Wu, Jiajing Shen, Meng Xuan, Qi Yang, Xiaoniu Zhejiang University of Technology Institute of Cyberspace Security College of Information Engineering Hangzhou310023 China ZJUT Binjiang Institute of Artificial Intelligence Hangzhou310056 China Fudan University Adaptive Networks and Control Lab Department of Electronic Engineering School of Information Science and Technology Shanghai200433 China Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China Shenzhen518066 China National Key Laboratory of Electromagnetic Space Security Jiaxing314033 China

Due to the decentralized and public nature of the blockchain ecosystem, malicious activities on the Ethereum platform impose immeasurable losses on users. At the same time, the transparency of cryptocurrency transactions provides a unique opportunity to analyze illegal activities, such as phishing scams, from a network perspective. Most existing phishing scam detection methods focus primarily on analyzing account interaction networks, which limits their ability to uncover transaction behavior patterns embedded within transaction interactions. To address this, we construct the Transaction SubGraph Network (TSGN) by using transaction subgraphs as basic elements and further propose a novel framework for Ethereum phishing account detection. Specifically, we rebuild the graph structures via three well-designed mapping mechanisms, yielding TSGN and its two variants, i.e., Directed-TSGN and Temporal-TSGN, to obtain direction-aware and time-aware transfer flow features. By further incorporating the mapping strategy into transaction multidigraphs, we develop the Multiple-TSGN, which could preserve more transaction flow features while concurrently reducing the time consumption of modeling large-scale networks. TSGN models based on transaction subgraph interactions can capture complex higher-order dependencies, which lay beyond the reach of models that exclusively capture pairwise account interactions. As a general framework, our model can incorporate various feature extraction methods to improve the performance of phishing detection. Extensive experimental results on Ethereum datasets show that our method achieves superior performance in phishing detection, yielding 3.27%∼6.71% relative improvement over previous state-of-the-art. © 2004-2012 IEEE.

关键词： Phishing

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Compatible-invariant subset analysis of deterministic finite automata via semi-tensor product of matrices approach

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The Journal of China Universities of Posts and Telecommunications 2018年第5期25卷 75-82页

作者： Zhang Zhipeng Chen Zengqiang Liu Zhongxin College of Computer and Control Engineering Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University

The compatible-invariant subset of deterministic finite automata（ DFA） is investigated to solve the problem of subset stabilization under the frameworks of semi-tensor product（ STP） of matrices. The concepts of compatibleinvariant subset and largest compatible-invariant subset are introduced inductively for Moore-type DFA,and a necessary condition for the existence of largest compatible-invariant subset is given. Meanwhile,by using the STP of matrices,a compatible feasible event matrix is defined with respect to the largest compatible-invariant *** on the concept of compatible feasible event matrix,an algorithm to calculate the largest compatible-invariant subset contained in a given subset is proposed. Finally,an illustrative example is given to validate the results.

关键词： discrete event dynamical systems (DEDSs) finite automata compatible iuvariant semi-tensor product (STP) compatible feasible eventmatrix

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Pose-graph optimization for efficient tie-point matching and 3D scene reconstruction from oblique UAV images

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ISPRS Journal of Photogrammetry and Remote Sensing 2025年 225卷 461-491页

作者： Zhihua Xu Yongze Niu Jincheng Jiang Rongjun Qin Ximin Cui College of Geoscience and Surveying Engineering China University of Mining and Technology-Beijing Beijing 100083 China North Automatic Control Technology Institute Taiyuan Shanxi 030006 China School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen Guangdong 518107 China Department of Civil Environmental and Geodetic Engineering The Ohio State University 2036 Neil Avenue Columbus OH 43210 USA Department of Electrical and Computer Engineering The Ohio State University Dreese Laboratories 205 2015 Neil Ave Columbus OH 43210 United States Translational Data Analytics Institute The Ohio State University 1760 Neil Ave Columbus OH 43210 United States

Oblique photogrammetry using unmanned aerial vehicles (UAV) is crucial to 3D scene reconstruction. Nevertheless, oblique images are generally acquired with large overlaps, and sometimes with multiple views. Although this increases the level of data completeness, it introduces additional and sometimes redundant computations in tie-point matching, creating overly dense camera connections in the pose graph for bundle adjustment (BA). This study optimizes the pose graph of oblique UAV images by removing redundant image connections to guide tie-point matching. Assuming a five-camera system for oblique image collection, a pose graph called a topologically connected camera network (TCN) was initially constructed using position and orientation system (POS) data to determine the spatial connectivity among oblique images. Second, five geometric meta-parameters of overlapping images were constructed, and their influence on tie-point matching was analyzed using a data-driven approach to generate a weighted pose graph. Third, the weighted pose graph was simplified to a degree-bounded skeletal camera network (D-SCN) using the proposed two-stage multi-objective graph optimization approach. Finally, the D-SCN was embedded into a structure from motion (SfM) pipeline to produce a novel D-SCN–SfM method to reduce the required computations for tie-point matching. The proposed D-SCN-SfM method was tested using data from three large sites, each containing over 5,000 images. In addition, the D-SCN-SfM method was compared with three state-of-the-art methods. The experimental results indicate that our method can significantly reduce the required computations for tie-point matching to 1/14–1/20 as compared to a method that uses only topological constraints, that is, TCN, saving 89–92% of the time expenditure. Furthermore, the accuracy and completeness of the 3D geometry produced by the proposed method were comparable to those produced by standard SfM methods. The source code of our approach

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Observer-based Adaptive Fuzzy control for a Class of Nonlinear Time-delay Systems

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International Journal of Automation and computing 2013年第4期10卷 275-280页

作者： Hassan A. Yousef Mohamed Hamdy Department of Electrical and Computer Engineering College of Engineering Sultan Qaboos University Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menofia University

An observer-based adaptive fuzzy control is presented for a class of nonlinear systems with unknown time delays. The state observer is first designed, and then the controller is designed via the adaptive fuzzy control method based on the observed states. Both the designed observer and controller are independent of time delays. Using an appropriate Lyapunov-Krasovskii functional, the uncertainty of the unknown time delay is compensated, and then the fuzzy logic system in Mamdani type is utilized to approximate the unknown nonlinear functions. Based on the Lyapunov stability theory, the constructed observer-based controller and the closed-loop system are proved to be asymptotically stable. The designed control law is independent of the time delays and has a simple form with only one adaptive parameter vector, which is to be updated on-line. Simulation results are presented to demonstrate the effectiveness of the proposed approach.

关键词： Observer adaptive fuzzy control nonlinear systems time delay stability.

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A Hybrid Data-Driven Granular Model for Battery Remaining Useful Life Prediction

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Jing, TaiLong Du, Sheng Wang, Cong Wu, Chao Pedrycz, Witold Sharaf, Mohamed Li, ZhiWu Luoyang Institute of Science and Technology School of Electrical Engineering and Automation Luoyang471023 China China University of Geosciences School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi’an710072 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland King Saud University College of Engineering Department of Industrial Engineering Riyadh11421 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau China

Accurate and meaningful prediction of the remaining useful life (RUL) of lithium-ion batteries (LIBs) provides a significant guide for the maintenance and management of these LIBs. A singular numerical predictive result by numerous conventional models is insufficient to furnish decision-makers with comprehensive or nuanced insights. To address this issue, predictive RUL results in the form of information granules are essential. In this study, a hybrid data-driven granular model is established for battery RUL prediction with granular (interval-based) quantification for LIBs. This granular model is designed and formulated in a way that it produces comprehensive prediction outcomes realized as information granules, which are expressed in a more descriptive and comprehensive manner. Thus, the resulting information granules can effectively reflect and communicate the confidence associated with the predictions. The granular model is realized in two steps: 1) probabilistic prediction results are produced by a hybrid numeric predictive model and 2) a comprehensive granulation of the probabilistic results is achieved under the principle of information granularity. The granular predictive results are holistically evaluated and optimized by the two associated criteria of granularity (coverage and specificity). This transformation of information granules provides an intuitive and interpretable display for battery maintenance and safe work. The proposed granular model is verified by using an open-access LIBs dataset, and the experimental results demonstrate that the proposed granular model outperforms other comparative methods. © 2025 IEEE. All rights reserved.

关键词： Prediction models

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Constrained Optimization with Decision-Dependent Distributions

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IEEE Transactions on Automatic control 2025年

作者： Wang, Zifan Liu, Changxin Parisini, Thomas Zavlanos, Michael M. Johansson, Karl H. KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures StockholmSE-10044 Sweden East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Imperial College London Department of Electrical and Electronic Engineering LondonSW7 2AZ United Kingdom Aalborg University Department of Electronic Systems Denmark University of Trieste Department of Engineering and Architecture Italy Duke University Department of Mechanical Engineering and Materials Science DurhamNC United States

In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization problems with decision-dependent distributions has assumed either the absence of constraints or fixed constraints. This work considers a more general setting where the constraints can also dynamically adjust in response to changes in the decision variables. Specifically, we consider linear constraints and analyze the effect of decision-dependent distributions in both the objective function and constraints. Firstly, we establish a sufficient condition for the existence of a constrained equilibrium point, at which the distributions remain invariant under retraining. Moreover, we propose and analyze two algorithms: repeated constrained optimization and repeated dual ascent. For each algorithm, we provide sufficient conditions for convergence to the constrained equilibrium point. Furthermore, we explore the relationship between the equilibrium point and the optimal point for the constrained decision-dependent optimization problem. Notably, our results encompass previous findings as special cases when the constraints remain fixed. To show the effectiveness of our theoretical analysis, we provide numerical experiments on both a market problem and a dynamic pricing problem for parking based on real-world data. © 1963-2012 IEEE.

关键词： Optimization algorithms

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