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Non-fragile [formula omitted] filtering for delayed discrete-time Markov jump systems: An adaptive event-triggered strategy J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Weifeng Xia, Lei Zhang, Jiajun Ma, Yongmin Li, Shuxin Du
This paper deals with the problem of non-fragile filter for delayed discrete-time Markov jump systems. The purpose is to design a mode-dependent filter such that the result filtering error system is stochastically stable and satisfies a prescribed performance lever . In order to improve the data transmission efficient, an adaptive event-triggered strategy is introduced. Then, with the help of the Lyapunov
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Admissibility LMI criteria for descriptor fractional-order systems with a changeable number of decision variables J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Ying Di, Jin-Xi Zhang, Xuefeng Zhang
This paper studies the admissibility problem of descriptor fractional-order systems (DFOSs) with order in . Firstly, an approach to stability for FOSs is derived which is effective for the case of at least two complex matrix variables. Secondly, based on the generalized linear matrix inequality (GLMI) region, a new admissibility criterion for DFOSs with multiple choices for the number of decision variables
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Identification and analysis of stochastic deception attacks on cyber physical systems J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Soheila Barchinezhad, Mohammad Sayad Haghighi, Vicenç Puig
Cyber Physical Systems (CPSs) refer to control systems which are composed of sensors, actuators, computers and network components. These systems are vulnerable to unforeseen failures and external malicious attacks. In this paper, we analyze the stability of CPSs under stochastic deception attacks. To this end: (i) we propose a statistical Intrusion Detection System (IDS) for detection of deception
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Hybrid dynamic event-triggered leader-following consensus for multi-agent systems with external disturbances J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Denghao Pang, Yechen Guo, Jinde Cao, Xiao-Wen Zhao, Hao Meng
Herein, we address the leader-following consensus for multi-agent systems with a directed graph while considering external disturbances. To optimize resource utilization, we propose a hybrid dynamic event-triggered mechanism (HDETM) that minimizes the inter-agent communication and reduces the frequency of controller updates. Furthermore, regularization techniques are employed to ensure that the considered
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Learning strategies for underwater robot autonomous manipulation control J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Hai Huang, Tao Jiang, Zongyu Zhang, Yize Sun, Hongde Qin, Xinyang Li, Xu Yang
Autonomous manipulation operations represent the high intelligent coordination from robotic vision and control, it is also a symbol of the advances of robotic intelligence. The limitations of visual sensing and the increasingly complex experimental conditions make autonomous manipulation operations more difficult, particularly for deep reinforcement learning methods, which can enhance robotic control
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Observer-based MPC for fuzzy cyber–physical system with hybrid attacks via a dynamic event-triggered mechanism J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-19 Cancan Wang, Qing Geng, Fucai Liu, Lining Fu
In this article, a secure model predictive control (MPC) algorithm is addressed for a nonlinear cyber–physical system (CPS) subject to hybrid attacks and parameter uncertainties via a dynamic event-triggered mechanism (DETM). The nonlinear CPS with parameter uncertainties is represented by the interval type-2 Takagi–Sugeno (IT2 T–S) fuzzy model. Considering that the full states of system are unmeasurable
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Minimum cost control of weighted networked evolutionary games with switched topologies and threshold J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-18 Yue Wu, Lulu Li, A.S. Alofi
Networked evolutionary games (NEGs) are a class of models that capture the interactions and evolution of strategies among rational agents in a network. In this paper, we study the problem of minimum cost control of NEGs with switched topologies and threshold, where the network structure can change over time and the agents have a minimum payoff requirement to survive. Using the semi-tensor product (STP)
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Quantized and event-triggered modeling and fault detection for networked fuzzy systems J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-18 Ziran Chen, Ziqi Cui, Hongtao Sun, Cheng Tan
This article concentrates on the issue of fault detection in the networked system. Quantized output and event-triggered communication scheme are absorbed into the system analysis, and consequently, by designing a new quantizer with event triggering mechanism, a smooth communication environment without undesired system data is guaranteed. And the imperfect information interaction strategy induced asynchronous
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Anti-delay Kalman filter fusion algorithm for inter-vehicle sensor network with finite-step convergence J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-18 Hang Yu, Yao Zou, Qingyu Li, Jie Zhu, Haojie Li, Sipei Liu, He Zhang, Keren Dai
Intelligent vehicle applications in autonomous driving and obstacle avoidance commonly require the precise relative state of vehicles. Accordingly, this study focuses on the coordinate fusion of vehicle state problem experienced by an inter-vehicle sensor network with time-varying transmission delays. Using the ingeniously designed low-complexity integration with a consensus strategy and buffer technology
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Biased regression algorithms in the quaternion domain J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-18 Rosa María Fernández-Alcalá, José Domingo Jiménez-López, Jesús Navarro-Moreno, Juan Carlos Ruiz-Molina
The ill-conditioned matrix problem in quaternion linear regression models is addressed in this paper and several dimension-reduction based regression methods for circumventing this problem are suggested. The algorithms are formulated in a general way and can be easily adapted to different scenarios: widely linear, semi-widely linear and strictly linear processing, in accordance with the properness
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Event-triggered-based encoding–decoding consensus control of continuous-time multi-agent systems under DoS attacks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-18 Rongmei Li, Chang-E Ren
The security of multi-agent systems (MASs) is important particularly when considering the potential threat posed by malicious attackers. Specifically, network attacks and information theft caused by attackers have garnered significant attention due to their potential to destroy the consensus of the system. Therefore, this paper presents a novel approach to achieve leader-following consensus control
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Command Filter-Based Event-Triggered Fixed-Time Control for Nonlinear Systems with Prescribed Performance and Actuator Faults J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-17 Yasaman Salmanpour, Mohammad Mehdi Arefi
This paper investigates command filter-based adaptive neural network (NN) minimal learning practical fixed-time control for stochastic nonlinear systems with prescribed performance and actuator faults. The considered system is in a high-order nonstrict-feedback stochastic structure with unknown dynamics and external disturbances. By combining NN with minimal learning parameter method, the need for
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NIRK-based mixed-type accurate continuous-discrete Gaussian filters with deterministically sampled expectation and covariance for state estimation in continuous-time stochastic process models with discrete measurements J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-16 G.Yu. Kulikov, M.V. Kulikova
This paper advances further the idea of overall continuous-discrete Gaussian filtering with deterministically sampled expectation and covariance towards efficient mixed-type accurate Kalman-like schemes based on self-regulated (ODE) solvers with automatic local and global error controls intended for treating continuous-time nonlinear stochastic process models with discrete measurements. The universal
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Event-triggered prescribed-time tracking for uncertain nonlinear systems with unknown control gain and output constraints J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-16 Quan Wan, Tianpeng Fan, Zhongguo Li, Zhengtao Ding
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Event-based adaptive secure asymptotic tracking control for nonlinear cyber–physical systems against unknown deception attacks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-16 Yongjie Tian, Ning Zhao
This article addresses the event-triggered adaptive neural network asymptotic tracking control problem for a class of nonlinear cyber–physical systems under unknown deception attacks. In the process of recursive design, a novel adaptive asymptotic tracking control strategy is proposed based on bound estimation method, backstepping technique and some smooth functions. The designed asymptotic tracking
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Critical-time metric for risk analysis against sharp input anomalies: Computation and application case study J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-15 Arthur Perodou, Christophe Combastel, Ali Zolghadri
This paper investigates the critical-time criteria as a security metric for controlled systems subject to sharp input anomalies (attacks, faults), characterized by high impact in a reduced amount of time (e.g. denial-of-service, upper saturation attack). The critical-time is the maximum time horizon for which a system can be considered to be safe after the occurrence of an anomaly. This metric is expected
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Improved asynchronous fault detection filter design for singular fuzzy Markovian jump systems against multi-cyber-attacks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-15 Yuxin Lou, Mengzhuo Luo, Jun Cheng, Kaibo Shi, Iyad Katib
This paper delves into the design of an asynchronous Fault Detection Filter (FDF) for Singular Fuzzy Markovian Jump Systems (SFMJSs), particularly under the influence of multi-cyber-attacks, leveraging an enhanced adaptive event-triggered mechanism (AETM). Initially, a Hidden Markovian Model (HMM) is employed to characterize the asynchronous interactions between SFMJSs and FDF. Subsequently, a mode-dependent
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Asynchronous dissipative control of time-delay singular Markovian jump systems with actuator saturation J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-15 Qian Zhang, Huaicheng Yan, Yongxiao Tian, Ping Qi
This paper focuses on the problem of asynchronous dissipative control for time-delay singular Markovian jump systems (SMJSs) with actuator saturation. In order to describe the asynchronous phenomenon between the system and the controller, a hidden Markov model (HMM) is adopted. In addition, the problem of actuator saturation is considered. Firstly, by the mode-dependent Lyapunov function, some novel
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Dynamic event-triggered fault detection for multi time scale systems: Application to grid connected converters J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-15 Jiantao Shi, Shaodong Gu, Shuangqing Xing, Chuang Chen
This paper deals with the fault detection problem for multi time scale systems. To save network resources, a novel dynamic event-triggered protocol with more generality and higher flexibility of parameters is proposed. The main novelties are condensed as follows, firstly, a modified fault detection observer and a quadratic residual evaluation function are synthetically designed; secondly, the sufficient
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Stability analysis of discrete-time delayed systems via matrix-injection-based transformation method for bivariate quadratic functions J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Ke-You Xie, Xing-Chen Shangguan, Hong-Zhang Wang, Li Jin
In this paper, the stability analysis of discrete-time systems with a time-varying delay is studied. First, a selectable matrix-injection-based transformation lemma is proposed to guarantee the negative (or positive) definiteness of bivariate quadratic function. This lemma allows a selection of conditions that combine different delay sets, which is more relaxed than that in most previous studies. Then
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Low-rank balanced truncation of discrete time-delay systems based on Laguerre expansions J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Ya-Xin Fang, Zhi-Hua Xiao, Zhen-Zhong Qi
This paper introduces a novel model order reduction method based on low-rank Gramian approximations for discrete time-delay systems. Firstly, an efficient algorithm based on Laguerre functions to compute the low-rank decomposition factors of the controllability and observability Gramians for discrete time-delay systems is given, in which the low-rank factors satisfy the iterative recursive formulas
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Semantic communication for cooperative perception based on importance map J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Yucheng Sheng, Hao Ye, Le Liang, Shi Jin, Geoffrey Ye Li
Cooperative perception, which has a broader perception field than single-vehicle perception, has played an increasingly important role in autonomous driving to conduct 3D object detection. Through vehicle-to-vehicle (V2V) communication technology, various connected automated vehicles (CAVs) can share their sensory information (LiDAR point clouds) for cooperative perception. We employ an importance
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Adaptive neural network backstepping control method for aerial manipulator based on coupling disturbance compensation J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Hai Li, Zhan Li, Jiayu Liu, Xiaolong Zheng, Xinghu Yu, Okyay Kaynak
The aerial manipulator, designed for complex aerial tasks, encounters multifaceted operational environments influenced by various internal and external disturbances. This paper introduces an adaptive neural network backstepping control technique fortified with coupling disturbance compensation to enhance the resilience of the aerial manipulator against these disturbances. Firstly, we propose a cutting-edge
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Distributed vehicular platoon control considering communication delays and packet dropouts J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Zhiping Shen, Yonggui Liu, Zeming Li, Yilin Wu
The influence of both inter–vehicular communication delays and packet dropouts on platoon control performance is studied. First, the conditions for achieving platoon mean square stability (MSS) are derived for three cases: undirected information flow (UIF) topology with time delays and identical packet losses, general information flow topology (IFT) with time delays and identical packet losses, and
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Optimal leader-following consensus under switching topologies based on event-triggered NN-based observer J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Zhen-Wei Yu, Li Ding, Zheng-Min Kong, Zhi-Wei Liu
This paper proposes a novel control strategy for multi-agent systems (MASs) to achieve optimal leader-following consensus under jointly connected topologies. The devised approach incorporates two key components: an event-triggered neural network (NN)-based leader observer and an NN-based optimal controller. The proposed leader observer allows followers to locally reconstruct the leader’s dynamics,
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Identification of edge removal fault in Boolean networks and disjunctive Boolean networks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Wenrong Li, Haitao Li, Xinrong Yang
It is meaningful to identify various faults occurring in dynamic systems as early as possible. This paper explores the identification of edge removal fault in Boolean networks (BNs). At first, with the help of semi-tensor product of matrices, the algebraic formulation is presented for the faulty BNs subject to an edge removal fault. After that, a fault-triggered matrix is constructed to uncover the
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Three-dimensional tracking of a transmitter under conic angle-frequency measurements of linear array sonars J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-13 Jonghoek Kim
This study considers tracking an underwater transmitter using a linear array sonar. The linear array sonar measures both the transmitter’s frequency and the conic angle with respect to the array’s direction. By analyzing the transmitter’s conic angle and frequency, the array sonar sensor estimates the transmitter’s three-dimensional position and (constant) velocity. This tracking problem is termed
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Lyapunov-based control system design for trajectory tracking in electrical autonomous vehicles with in-wheel motors J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Hamid Rahmanei, Abbas Aliabadi, Ali Ghaffari, Shahram Azadi
In this paper, a hierarchical three-layer control structure is presented for the vehicles path following. In the first layer, a Lyapunov-based control law is proposed for determining forces and torque required at the vehicles center of gravity that guarantees the convergence of tracking errors. Then, a feasible formulation is developed to distribute the longitudinal and lateral forces of the wheels
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Improved DRL-based energy-efficient UAV control for maximum lifecycle J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Haixu Ma, Guang Yang, Xuxu Sun, Dongming Qu, Guanyu Chen, Xueying Jin, Ning Zhou, Xinxin Liu
Unmanned aerial vehicles (UAVs) operating as airborne base stations (UAV-BSs) provide efficient on-demand services to ground users. UAV-BSs are inherently flexible and mobile, allowing them to be strategically deployed based on ground user distribution and quality of service requirements, including coverage rate, system lifecycle, and user fairness. Owing to the limited battery capacity and coverage
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Data-driven ensemble optimal compensation control for partially known delayed and persistently disturbed nonlinear systems J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Xuyang Guo, Changzhu Zhang, Hao Zhang, Seungyong Han, Suneel Kumar Kommuri, Zhuping Wang
In almost all industrial processes, the development of an accurate mathematical model that comprehensively characterizes the regulated system poses a substantial obstacle. Diverse factors, such as unidentified system components and time-varying external disturbances, contribute to this phenomenon. This can result in a disparity between the model and the plant and thereby compromising the performance
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Dissipative PID control for uncertain positive Roesser system under the try-once-discard protocol J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Na Zhang, Jinling Liang
This paper addresses the problem of dissipative proportional–integral–derivative (PID) control for the delayed positive Roesser system with interval uncertainties under the try-once-discard (TOD) protocol. To alleviate the undesired data congestion phenomenon in the shared communication network, the TOD protocol is introduced to regulate which sensor node could release its measurement at each transmission
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Finite-time stability of equilibrium point of a class of fractional-order nonlinear systems J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Zaiyong Feng, Zhengrong Xiang
This paper studies the finite-time stability (FTS) of equilibrium point of a class of fractional-order nonlinear systems (FONSs) described by Caputo fractional-order derivative (CFOD). The definition of finite-time equilibrium point (FTEP) is proposed for the FONSs, and it is proved that the CFOD of the FTEP is not constantly equal to 0. A sufficient and necessary condition on the FTEP is proposed
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Deep learning based 2D-DOA estimation using L-shaped arrays J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Alireza Fadakar, Ashkan Jafari, Parisa Tavana, Reza Jahani, Saeed Akhavan
Direction-of-arrival (DOA) estimation problems arise in many applications such as wireless communication and localization. Recently, a number of deep learning (DL) based methods have been studied for one dimensional (1D) DOA estimation with relatively fewer studies for 2D-DOA estimation. In this study, we propose a low-complexity DL based method to estimate both elevation and azimuth DOAs of sources
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Multisource disturbances rejection control for linear systems with unmeasured states under process and measurement disturbances J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Yankai Li, Ding Liu, Dongping Li, Qingyu Wang, Chen Chen
In this paper, a multisource disturbances attenuation and rejection control method is proposed for linear systems with unmeasured states under process and measurement disturbances. Since some internal states of control systems are hard to be measured via sensors in the realistic engineering process, a novel output feedback control scheme is proposed for designing the anti-disturbance controller by
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Asynchronous deep reinforcement learning with gradient sharing for State of Charge balancing of multiple batteries in cyber–physical electric vehicles J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-11 Pengcheng Chen, Shichao Liu, Hicham Chaoui, Bo Chen, Li Yu
This work targets the State of Charge (SoC) imbalance issue due to the mismatch across multiple batteries in cyber–physical electric vehicles (EVs) arisen from a variety of practical factors such as manufacturing tolerance, nonuniform aging process and uneven operation temperature. While most of existing SoC balancing approaches are model-based and require accurate prior knowledge, a data-driven asynchronous
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[formula omitted] gain-scheduled dynamic output feedback control with transient performance applied to electrical microgrid J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-10 R.M. Fuentes, M.J. Lacerda, C.F. Morais, R.C.L.F. Oliveira, J.M. Palma
This paper introduces an approach for designing gain-scheduled dynamic output feedback controllers for continuous-time Linear Parameter-Varying (LPV) systems. The aim is to improve transient response by incorporating both -stability and criteria into the synthesis conditions. We achieve this by employing changes in variables and congruence transformations, which lead to new synthesis conditions expressed
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Collision avoidance control for limited perception unmanned surface vehicle swarm based on proximal policy optimization J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-10 Mengmeng Yin, Yiyun Zhao, Fanbiao Li, Bin Liu, Chunhua Yang, Weihua Gui
In order to ensure the safe and coordinated operation of unmanned surface vehicle (USV) swarm in complex marine environments, the primary problem is collision avoidance control (CAC). However, the limited perception, environmental uncertainty and multi-source complexity bring significant challenges to the efficient collaboration and CAC of the USV swarm. To overcome the above challenges, this paper
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Optimal synchronization for multi-agent systems: A performance-dependent switching topology J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-09 Yiwen Qi, Yunlong Wang, Honglin Geng, Ning Xing, Zonghua Zheng, He Li
This paper proposes an optimal output synchronization control method for heterogeneous multi-agent systems (HMASs) under a performance-dependent switching topology and DoS attacks. First, local and global switched performance index functions (SPIF) and SPIF-dependent topology switching law are proposed, respectively, thus, the control performance and topology quality can be quantitatively expressed
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Stochastic differential game of joint emission reduction in the supply chain based on CSR and carbon cap-and-trade mechanism J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-09 Ke Wang, Panyu Wu, Weihai Zhang
This paper considers both carbon emission reduction and corporate social responsibility (CSR) goodwill as endogenous variables in the joint emission reduction process of the supply chain system. The joint emission reduction strategy of the three-tier supply chain system is examined from a long-term perspective utilizing stochastic differential game models. Three models, namely the cooperative game
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Prediction of cutterhead torque change trend of shield machine based on partial state visible HMM and LSTM J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-08 Xuanyu Liu, Mengting Jiang, Cheng Shao, Yudong Wang, Qiumei Cong
Cutterhead torque is a key parameter to determine the normal operation of shield machine. Accurately predicting the change trend of cutterhead torque can provide decision support for shield operators to control operating parameters. Therefore, a prediction method of cutterhead torque change trend based on partial state visible Hidden Markov Model (HMM) and Long Short-Term Memory (LSTM) network is proposed
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Max-consensus of multi-agent systems in random networks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-08 Jianing Yang, Liqi Zhou, Bohui Wang, Yuanshi Zheng
This paper considers max-consensus of a discrete-time multi-agent system (MAS) in directed random networks. Interactions among agents in the MAS are probabilistic and independent with each other. By using max-plus algebra and random theory, a sufficient and necessary condition is given for achieving max-consensus of the MAS. Moreover, we demonstrate that the max-consensus in four probabilistic senses
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A pre-defined finite time neural solver for the time-variant matrix equation [formula omitted] J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-07 Yuhuan Chen, Jingjing Chen, Chenfu Yi
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Observer-based secure consensus tracking of positive multi-agent systems under periodic denial-of-service attacks J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-07 Xin Gong, Zhipeng Zhang, Yukang Cui, Shi Liang
This paper investigates the problem of secure consensus tracking for positive multi-agent systems (MASs) under periodic denial-of-service (DoS) attacks, where DoS attacks usually impede the transmission of signals between agents. The considered DoS attacks in this paper are assumed to recur periodically, guided by a time-sequence approach. Firstly, an observer-based output-feedback consensus tracking
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Data driven secure control for cyber–physical systems under hybrid attacks: A Stackelberg game approach J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-07 Cheng Fei, Jun Shen, Hongling Qiu, Zhipeng Zhang
This article presents a model-free Q-Learning algorithm for addressing the optimal control problem in cyber–physical systems (CPS) exposed to denial-of-service (DoS) attacks and false data injection (FDI) attacks. The problem is formulated as a non-cooperative game within the framework of the Stackelberg game, in which the control strategy acts as the leader, while the FDI attacks strategy serves as
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Adaptive Cartesian space control of robotic manipulators: A concurrent learning based approach J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-06 Serhat Obuz, Enver Tatlicioglu, Erkan Zergeroglu
This work introduces a concurrent learning-based adaptive control design for end-effector tracking and the corresponding stability analysis for robotic manipulators. The presented controller is developed directly in Cartesian space, thereby removing the necessity for inverse kinematics calculations at the position level. The designed adaptive controller ensures global exponential tracking of the end-effector
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Optimized backstepping consensus control using adaptive observer-critic–actor reinforcement learning for strict-feedback multi-agent systems J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-06 Jiahao Zhu, Guoxing Wen, Kalyana C. Veluvolu
In this paper, we present a novel control method, combining observer-based optimized backstepping (OB) control, reinforcement learning (RL) strategy, and adaptive neural networks (NN), for strict-feedback multi-agent systems with unmeasurable states. The primary objective is to enhance the overall system backstepping controller by optimizing both virtual and actual controllers for corresponding subsystems
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Nonsingular finite-time heading tracking control of marine vehicles with tracking error constraints J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-06 Yanli Liu, Yihua Sun, Li-Ying Hao
This brief copes with the finite-time heading tracking control for marine vehicles. The tracking error constraints, stochastic disturbance and dead-zone output are simultaneously taken into consideration in the controlled systems. To manage the dead-zone output issue, a smooth approximation model is brought in to offset the nondifferentiable phenomena during the control, besides, the adaptive technique
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Nonfragile robust [formula omitted] containment control for multi-agent systems with a time-varying delay J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-06 Tuo Zhou, Chongyang Liu, Wei Wang
Under a fixed directed graph, this paper is concerned with the distributed nonfragile robust containment control of linear multi-agent systems with model uncertainty subject to admissible external disturbances in the presence of communication delay. Compared with the situation where the controller only considers either nonfragility or time delay, a class of controller considering both nonfragility
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Improved sliding-mode control for a class of disturbed systems based on a disturbance observer J. Franklin Inst. (IF 4.1) Pub Date : 2024-03-01 Baozeng Fu, Weiwei Che, Qingzhi Wang, Yongchao Liu, Haisheng Yu
The stabilization problem for a class of disturbed systems is dealt with by proposing an improved sliding-mode control (SMC) scheme in this paper. Through designing a new time-varying switching gain and a sliding surface, a nonlinear disturbance observer (DOB)-based improved SMC is developed to counteract disturbances’ influence on the system and make the closed-loop system asymptotically stable. The
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Impact time and angle guidance considering aerodynamic drag J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-29 Honglong Kang, Pengyu Wang, Chang-Hun Lee, Shenmin Song
This paper presents a new guidance law for homing missiles to achieve the impact time and angle control against a stationary target in the presence of aerodynamic drag. As a first step, an impact angle guidance law is developed based on the framework of conventional proportional navigation guidance. The novelty of the proposed impact angle guidance law is that its trajectory shape and length are independent
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Adaptive velocity control of an autonomous vehicle using input-error model reference approach J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-29 Abolfazl Simorgh, Abolhassan Razminia, Arash Marashian
The input error model reference adaptive control (IE-MRAC) is employed to regulate the longitudinal velocity of an autonomous vehicle to desired values by controlling both the throttle and the braking system. The proposed method deals with matching the unknown longitudinal model of the vehicle with a predefined model in the presence of various disturbances, including road conditions and aerodynamic
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Fuzzy asynchronous fault detection for Markov jump systems with quantization and partially unknown transition probabilities J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-29 Li-Xiang Feng, Guang-Hong Yang
This paper investigates the asynchronous fault detection (FD) problem for discrete-time interval type-2 (IT2) fuzzy Markov jump systems with quantization and partially unknown transition probabilities. To describe the asynchronous phenomenon that the mode information of the system cannot be communicated immediately to the filter, a hidden Markov model is utilized. Considering the effects of quantization
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Adaptive event-triggered output feedback control for uncertain networked T–S fuzzy system with data loss and bounded disturbance: An efficient MPC strategy J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-28 Xiaoming Tang, Kun Zhao, Lei Zhang, Xiao Lv, Hongchun Qu
This paper proposes an adaptive event-triggered (AET) control, efficient model predictive control (EMPC) and output feedback control co-design approach for uncertain nonlinear systems over networks with bounded disturbance and data loss. The AET control involving a novel adaptive law is utilized to further reduce data transmission in networked control systems. Involving the technique of quadratic boundedness
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Asymmetric prescribed performance control for nonlinear systems under intermittent communication J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-28 Hao Liu, Wei-Wei Che
This paper considers the prescribed performance tracking control problem for strict-feedback nonlinear systems with asymmetric output constraints. A new performance function is constructed to achieve the asymmetric prescribed performance control with the characteristic of the asymmetric output constraint consideration. To save the communication resources in the controller-to-actuator channel, a relative
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Global stabilization of a bounded controlled system based on the Rössler system J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-28 Héctor Martínez, Julio Solís-Daun
In this work we present a method for the of an affine control system based on a Rössler system (which is well known by its chaotic behavior), through regular feedback controls constrained to control value sets given by (convex) polytopes . The proposed method for control designing is based on the () theory due to Artstein and Sontag. To this aim, we construct first an explicit to “trap” the global
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A control architecture for fixed-wing aircraft based on the convolutional neural networks J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-28 Yousef Seifouripour, Hadi Nobahari
This paper develops a nonlinear architecture to control different fixed-wing aircraft. This architecture has inner and outer loops. The inner loops, designed based on the convolutional neural networks, control the internal dynamics of the aircraft, and the outer loops, which use linear controllers, are designed to control the kinematic states, which are the same for all aircraft. So, the inner loops
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Backup Pattern for traction system of FWIA electric vehicle to guarantee maneuverability and stability in presence of motor faults and failures J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-27 Zhongchao Liang, Zhongnan Wang, Jianghua Duan, Jian Liu, Pak Kin Wong, Jing Zhao
Faults and failures in driving motors of four-wheel-independently-actuated (FWIA) electric vehicles can lead to hazardous accidents. To address this challenge, this paper introduces a novel “Backup Pattern” by grouping the driving motors into front and rear traction subsystems. This “Backup Pattern” ensures the optimal allocation of driving torque between functional motors, providing a reliable and
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A robust nonlinear tracking MPC using qLPV embedding and zonotopic uncertainty propagation J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-27 Marcelo M. Morato, Victor M. Cunha, Tito L.M. Santos, Julio E. Normey-Rico, Olivier Sename
In this paper, we propose a novel Nonlinear Model Predictive Control (NMPC) framework for tracking for piece-wise constant reference signals. The main novelty is the use of quasi-Linear Parameter Varying (qLPV) embeddings in order to describe the nonlinear dynamics. Furthermore, these embeddings are exploited by an extrapolation mechanism, which provides the future behaviour of the scheduling parameters
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Generalized singular spectrum analysis for the decomposition and analysis of non-stationary signals J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-27 Jialiang Gu, Kevin Hung, Bingo Wing-Kuen Ling, Daniel Hung-Kay Chow, Yang Zhou, Yaru Fu, Sio Hang Pun
Singular spectrum analysis (SSA) has been verified to be an effective method for decomposing non-stationary signals. The decomposition and reconstruction stages can be interpreted as a zero-phase filtering process where reconstructed components are obtained by inputting a signal through moving average filters. However, mathematical analysis indicates that the use of a default rectangular window in
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Energy shaping-based consensus control in networked underactuated Euler–Lagrange systems with communication and input delays J. Franklin Inst. (IF 4.1) Pub Date : 2024-02-24 Bin Zheng, Jinchen Ji, Runlong Peng, Zhonghua Miao, Jin Zhou
This paper aims to solve the problems of energy shaping-based consensus control in networked underactuated Euler–Lagrange systems (NUELSs) in the presence of communication and input delays. By appropriately introducing the auxiliary sliding mode variable describing local communication interaction among agents and the corresponding adaptive velocity observer in energy-shaping framework, two decentralized