Pub Date : 2026-02-01Epub Date: 2025-12-28DOI: 10.1016/j.jfranklin.2025.108354
N. Sakthivel, V. Rajkumar, S. Keerthna
This article is focused on the state estimation problem of nonlinear complex dynamical networks (CDNs) with the combination of Markovian switching parameters, exogenous disturbance, coupling delay and multiple cyber attacks. Precisely, the controller is designed with an event-triggered mechanism to obtain the synchronization of addressed CDNs, which reduces the burden of the communication channel and improves the implementation of bandwidth. Further, the event-triggered control technique is modeled with adversary attacks, namely, deception attacks and denial-of-service (DoS) attacks, which acquire the secure synchronization of the considered networks. By establishing a suitable Lyapunov–Krasovskii functional (LKF), novel adequate criteria have been obtained in the form of linear matrix inequalities (LMIs), which guarantee the secure synchronization of CDNs based on mixed H∞ and passivity performance. Ultimately, the obtained theoretical results are validated through numerical examples.
{"title":"Mixed H∞ and passivity based state estimation for Markovian switching complex dynamical networks with event-triggered control subject to multiple cyber attacks","authors":"N. Sakthivel, V. Rajkumar, S. Keerthna","doi":"10.1016/j.jfranklin.2025.108354","DOIUrl":"10.1016/j.jfranklin.2025.108354","url":null,"abstract":"<div><div>This article is focused on the state estimation problem of nonlinear complex dynamical networks (CDNs) with the combination of Markovian switching parameters, exogenous disturbance, coupling delay and multiple cyber attacks. Precisely, the controller is designed with an event-triggered mechanism to obtain the synchronization of addressed CDNs, which reduces the burden of the communication channel and improves the implementation of bandwidth. Further, the event-triggered control technique is modeled with adversary attacks, namely, deception attacks and denial-of-service (DoS) attacks, which acquire the secure synchronization of the considered networks. By establishing a suitable Lyapunov–Krasovskii functional (LKF), novel adequate criteria have been obtained in the form of linear matrix inequalities (LMIs), which guarantee the secure synchronization of CDNs based on mixed <em>H</em><sub>∞</sub> and passivity performance. Ultimately, the obtained theoretical results are validated through numerical examples.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108354"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-25DOI: 10.1016/j.jfranklin.2025.108374
Xiaoxiang Hu , Yuewen Wang , Jingwen Xu , Jingyan Zhao , Bing. Xiao
By considering the actuator rate constraint and measurable output of hypersonic flight vehicle’s (HFV) attitude system, a dynamic output feedback sliding mode learning controller (DOFSMLC) is proposed in this paper. The proposed DOFSMLC can solve the controller design of nonlinear system with incomplete measurable state, system uncertainties and input rate constraint simultaneously. The nonlinear model of HFV’s attitude system is firstly represented by T-S fuzzy model, then the actuator rate constraint is proposed. Based on the original tracking control objective of HFV’s attitude system, the control objective of the T-S fuzzy model is built. Then a dynamic output feedback (DOF) based sliding surface is design and the stability of the designing sliding surface is guaranteed by selecting appropriate dynamic feedback parameters. A traditional discontinuous reaching law is deigned without considering the actuator rate constraint, and then a sliding mode learning control (SMLC) with iterative updating law is designed. By the designed SMLC, the actuator rate constraint and the system stability requirements can be guaranteed synchronously. Finally, the proposed DOFSMLC is applied on the nonlinear model of HFV’s attitude system, and the simulation results validate the effectiveness of the presented controller
{"title":"Dynamic output feedback fuzzy sliding mode learning attitude control for hypersonic flight vehicle with actuator rate constraint","authors":"Xiaoxiang Hu , Yuewen Wang , Jingwen Xu , Jingyan Zhao , Bing. Xiao","doi":"10.1016/j.jfranklin.2025.108374","DOIUrl":"10.1016/j.jfranklin.2025.108374","url":null,"abstract":"<div><div>By considering the actuator rate constraint and measurable output of hypersonic flight vehicle’s (HFV) attitude system, a dynamic output feedback sliding mode learning controller (DOFSMLC) is proposed in this paper. The proposed DOFSMLC can solve the controller design of nonlinear system with incomplete measurable state, system uncertainties and input rate constraint simultaneously. The nonlinear model of HFV’s attitude system is firstly represented by T-S fuzzy model, then the actuator rate constraint is proposed. Based on the original tracking control objective of HFV’s attitude system, the control objective of the T-S fuzzy model is built. Then a dynamic output feedback (DOF) based sliding surface is design and the stability of the designing sliding surface is guaranteed by selecting appropriate dynamic feedback parameters. A traditional discontinuous reaching law is deigned without considering the actuator rate constraint, and then a sliding mode learning control (SMLC) with iterative updating law is designed. By the designed SMLC, the actuator rate constraint and the system stability requirements can be guaranteed synchronously. Finally, the proposed DOFSMLC is applied on the nonlinear model of HFV’s attitude system, and the simulation results validate the effectiveness of the presented controller</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108374"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145941329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-09DOI: 10.1016/j.jfranklin.2026.108401
Shengli Du , Qiong Wu , Honggui Han , Junfei Qiao
This paper investigates the fully distributed consensus control problem for nonlinear multiagent systems (MASs) subject to denial-of-service (DoS) attacks, external disturbances, and unmodeled nonlinearities. To mitigate the adverse effects of such uncertainties, a radial basis function neural network (RBFNN)-based adaptive control law is developed, combined with sign-function-based update rules to ensure robust approximation and compensation. In addressing the communication constraints induced by DoS attacks, a dynamic event-triggered switching control strategy is further proposed to reduce communication load while maintaining resilience against intermittent network failures. To eliminate the reliance on any global information, a fully distributed implementation is achieved, enhancing the scalability and practicality of the control scheme. With the assistance of Lyapunov stability theory, some bounded consensus conditions have been established. Finally, two simulation studies are conducted to demonstrate the effectiveness and robustness of the proposed control approach.
{"title":"Resilient adaptive NN-based distributed consensus for nonlinear MASs subject to DoS attacks and uncertainties","authors":"Shengli Du , Qiong Wu , Honggui Han , Junfei Qiao","doi":"10.1016/j.jfranklin.2026.108401","DOIUrl":"10.1016/j.jfranklin.2026.108401","url":null,"abstract":"<div><div>This paper investigates the fully distributed consensus control problem for nonlinear multiagent systems (MASs) subject to denial-of-service (DoS) attacks, external disturbances, and unmodeled nonlinearities. To mitigate the adverse effects of such uncertainties, a radial basis function neural network (RBFNN)-based adaptive control law is developed, combined with sign-function-based update rules to ensure robust approximation and compensation. In addressing the communication constraints induced by DoS attacks, a dynamic event-triggered switching control strategy is further proposed to reduce communication load while maintaining resilience against intermittent network failures. To eliminate the reliance on any global information, a fully distributed implementation is achieved, enhancing the scalability and practicality of the control scheme. With the assistance of Lyapunov stability theory, some bounded consensus conditions have been established. Finally, two simulation studies are conducted to demonstrate the effectiveness and robustness of the proposed control approach.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108401"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-03DOI: 10.1016/j.jfranklin.2025.108394
Shuo Liu , Huaguang Zhang , Hongbo Pang
This paper concerns on adaptive predefined-time asymptotic tracking control issume for switched uncertain nonlinear systems with switching deception attacks, although the output tracking control problem for each subsystem is not solvable. Switching deception attacks mode is constructed in channel of sensor-to-controller channel (S-C) and controller-to-actuatorb (C-A) firstly. A more general predefined-time stability criterion is established, which is an useful tool for predefined-time asymptotic tracking control. To overcome the disadvantage of recursive design methods, a predefined-time command filter has been constructed. Moreover, a predefined-time controller and a adaptive state dependent switching law dependent on adaptive parameter estimation are given to ensure that all the signals of the resulting closed-loop system subject to switching deception attacks are bounded. The tracking error can enter into the interval near origin in predefined time, and asymptotically tend towards to zero finally. To prevent the Zeno behavior, a hysteresis switching law dependent on parameter estimation is derived. Finally, an example on RLC circuite system is given to verty the effectiveness of the novel method.
{"title":"Adaptive predefined-time asymptotic tracking control for uncertain switched nonlinear systems with switching deception attacks","authors":"Shuo Liu , Huaguang Zhang , Hongbo Pang","doi":"10.1016/j.jfranklin.2025.108394","DOIUrl":"10.1016/j.jfranklin.2025.108394","url":null,"abstract":"<div><div>This paper concerns on adaptive predefined-time asymptotic tracking control issume for switched uncertain nonlinear systems with switching deception attacks, although the output tracking control problem for each subsystem is not solvable. Switching deception attacks mode is constructed in channel of sensor-to-controller channel (S-C) and controller-to-actuatorb (C-A) firstly. A more general predefined-time stability criterion is established, which is an useful tool for predefined-time asymptotic tracking control. To overcome the disadvantage of recursive design methods, a predefined-time command filter has been constructed. Moreover, a predefined-time controller and a adaptive state dependent switching law dependent on adaptive parameter estimation are given to ensure that all the signals of the resulting closed-loop system subject to switching deception attacks are bounded. The tracking error can enter into the interval near origin in predefined time, and asymptotically tend towards to zero finally. To prevent the Zeno behavior, a hysteresis switching law dependent on parameter estimation is derived. Finally, an example on RLC circuite system is given to verty the effectiveness of the novel method.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108394"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145915209","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-09DOI: 10.1016/j.jfranklin.2026.108415
Jiayu Zhao, Tao Zhao, Hainan Yang
Redundant manipulators are widely employed in complex and precision-critical tasks, yet achieving effective disturbance rejection remains challenging due to their highly nonlinear dynamics, strong inter-joint coupling, and susceptibility to both time- and batch-varying uncertainty disturbances. Existing iterative learning control approaches often struggle to cope with such disturbances, especially when these disturbances vary within each iteration cycle, which limits their applicability in repetitive high-accuracy tasks. To address this gap, this paper proposes an adaptive iterative learning control (AILC) scheme integrated with an interval type-2 fuzzy extended state observer (IT2FESO) to enhance both tracking accuracy and disturbance rejection performance. First, an interval type-2 fuzzy model of the manipulator is constructed via the fuzzy c-regression clustering algorithm to capture inherent nonlinearities and model uncertainties. Then, the IT2FESO is designed to estimate time- and batch-varying disturbances in real time, and its output is incorporated into the AILC to enable autonomous parameter adaptation and accurate target trajectory tracking. Finally, a compound energy function is formulated to rigorously establish the convergence conditions of the tracking errors. Simulation studies on a redundant manipulator demonstrate that the proposed approach achieves superior tracking accuracy and disturbance rejection performance under time- and batch-varying uncertainty disturbances.
{"title":"Extended state observer-based adaptive iterative learning control of redundant manipulators subject to dual-domain disturbances","authors":"Jiayu Zhao, Tao Zhao, Hainan Yang","doi":"10.1016/j.jfranklin.2026.108415","DOIUrl":"10.1016/j.jfranklin.2026.108415","url":null,"abstract":"<div><div>Redundant manipulators are widely employed in complex and precision-critical tasks, yet achieving effective disturbance rejection remains challenging due to their highly nonlinear dynamics, strong inter-joint coupling, and susceptibility to both time- and batch-varying uncertainty disturbances. Existing iterative learning control approaches often struggle to cope with such disturbances, especially when these disturbances vary within each iteration cycle, which limits their applicability in repetitive high-accuracy tasks. To address this gap, this paper proposes an adaptive iterative learning control (AILC) scheme integrated with an interval type-2 fuzzy extended state observer (IT2FESO) to enhance both tracking accuracy and disturbance rejection performance. First, an interval type-2 fuzzy model of the manipulator is constructed via the fuzzy c-regression clustering algorithm to capture inherent nonlinearities and model uncertainties. Then, the IT2FESO is designed to estimate time- and batch-varying disturbances in real time, and its output is incorporated into the AILC to enable autonomous parameter adaptation and accurate target trajectory tracking. Finally, a compound energy function is formulated to rigorously establish the convergence conditions of the tracking errors. Simulation studies on a redundant manipulator demonstrate that the proposed approach achieves superior tracking accuracy and disturbance rejection performance under time- and batch-varying uncertainty disturbances.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108415"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-12-18DOI: 10.1016/j.jfranklin.2025.108356
Zeinab Ebrahimi, Mohammad Deghat
This paper presents a distributed continuous-time optimization framework designed to address the challenges posed by time-varying cost functions, nonlinear inequality constraints, and equality constraints in multi-agent systems subject to disturbances. The proposed framework integrates log-barrier and quadratic penalty functions to handle constraints and employs an integral sliding mode control for disturbance rejection, including cases with bounded disturbances and disturbances with bounded derivatives. The proposed method ensures asymptotic convergence to the optimal solution, and convergence is established through nonsmooth analysis and Lyapunov theory. The effectiveness of the proposed algorithms is validated via numerical simulations on network topologies with different connectivity levels.
{"title":"Distributed continuous-time optimization with nonlinear inequality and equality constraints under disturbances","authors":"Zeinab Ebrahimi, Mohammad Deghat","doi":"10.1016/j.jfranklin.2025.108356","DOIUrl":"10.1016/j.jfranklin.2025.108356","url":null,"abstract":"<div><div>This paper presents a distributed continuous-time optimization framework designed to address the challenges posed by time-varying cost functions, nonlinear inequality constraints, and equality constraints in multi-agent systems subject to disturbances. The proposed framework integrates log-barrier and quadratic penalty functions to handle constraints and employs an integral sliding mode control for disturbance rejection, including cases with bounded disturbances and disturbances with bounded derivatives. The proposed method ensures asymptotic convergence to the optimal solution, and convergence is established through nonsmooth analysis and Lyapunov theory. The effectiveness of the proposed algorithms is validated via numerical simulations on network topologies with different connectivity levels.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108356"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, we propose an innovative approach to shadow removal in images by enhancing the space-variant anisotropic Partial Differential Equation (PDE) framework. This enhancement involves redefining existing osmosis models to incorporate tensor-based characteristics inspired by Weickert-type operators. The model leverages spatially distant pixel similarities, using a specified window size to improve image restoration. The numerical solution is obtained through the Split Bregman Iterative method (SBI). To thoroughly evaluate the model’s performance, we conduct a series of tests, including both perceptual and quantitative assessments. The results demonstrate that our approach outperforms state-of-the-art methods in shadow removal.
{"title":"Enhanced shadow removal using space-variant anisotropic PDEs and tensor-based osmosis models","authors":"Fakhr-Eddine Limami , Aissam Hadri , Amine Laghrib , Lekbir Afraites","doi":"10.1016/j.jfranklin.2025.108315","DOIUrl":"10.1016/j.jfranklin.2025.108315","url":null,"abstract":"<div><div>In this work, we propose an innovative approach to shadow removal in images by enhancing the space-variant anisotropic Partial Differential Equation (PDE) framework. This enhancement involves redefining existing osmosis models to incorporate tensor-based characteristics inspired by Weickert-type operators. The model leverages spatially distant pixel similarities, using a specified window size to improve image restoration. The numerical solution is obtained through the Split Bregman Iterative method (SBI). To thoroughly evaluate the model’s performance, we conduct a series of tests, including both perceptual and quantitative assessments. The results demonstrate that our approach outperforms state-of-the-art methods in shadow removal.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108315"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1016/j.jfranklin.2025.108387
Zhaoxia Duan , Yuyan Fu , Choon Ki Ahn , Zhengrong Xiang
This paper aims to design a fault detection (FD) filter for continuous two-dimensional (2-D) Markov jump positive systems (MJPSs) with constant state delays that ensures the stochastic stability and L1/ performances of the filtering augmented system. The L1-gain and performances of the delayed continuous 2-D MJPSs are investigated, and their exact values can be calculated. Necessary and sufficient conditions for ensuring the L1-gain performance and index of the system are derived. On this basis, sufficient conditions for the existence of the mixed FD filter are achieved and then are solved via an iterative algorithm. Finally, a numerical example validates the preceding theoretical findings.
{"title":"L1/L− fault detection filtering for delayed 2-D continuous positive Markov jump systems","authors":"Zhaoxia Duan , Yuyan Fu , Choon Ki Ahn , Zhengrong Xiang","doi":"10.1016/j.jfranklin.2025.108387","DOIUrl":"10.1016/j.jfranklin.2025.108387","url":null,"abstract":"<div><div>This paper aims to design a fault detection (FD) filter for continuous two-dimensional (2-D) Markov jump positive systems (MJPSs) with constant state delays that ensures the stochastic stability and <em>L</em><sub>1</sub>/<span><math><msub><mi>L</mi><mo>−</mo></msub></math></span> performances of the filtering augmented system. The <em>L</em><sub>1</sub>-gain and <span><math><msub><mi>L</mi><mo>−</mo></msub></math></span> performances of the delayed continuous 2-D MJPSs are investigated, and their exact values can be calculated. Necessary and sufficient conditions for ensuring the <em>L</em><sub>1</sub>-gain performance and <span><math><msub><mi>L</mi><mo>−</mo></msub></math></span> index of the system are derived. On this basis, sufficient conditions for the existence of the mixed <span><math><mrow><msub><mi>L</mi><mn>1</mn></msub><mo>/</mo><msub><mi>L</mi><mo>−</mo></msub></mrow></math></span> FD filter are achieved and then are solved via an iterative algorithm. Finally, a numerical example validates the preceding theoretical findings.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108387"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1016/j.jfranklin.2026.108411
Bin Lu , Lili Li , Jinqi Liu , Xiaowei Zhao
Deception attacks in switched systems can manipulate both the switching signal and system state, inducing severe asynchronous switching. While existing research predominantly employs passive mitigation strategies, this paper proposes a proactive secure control framework integrating prediction into attack detection. A model predictive control-based attack detection mechanism, augmented by a mode-state predictor, detects attacks by comparing predicted and received system modes and states. A detection-aware event-triggered mechanism and a mode-based try-once-discard protocol are implemented to reduce asynchrony between the subsystem and the controller. Additionally, an optimal subsystem switching rule, derived from the optimal states, ensures stability and security during switching. Asymptotic stability of the closed-loop system is analytically verified, and its feasibility is validated through an unmanned surface vehicle case study.
{"title":"Predictive-Deception-Attack-Detection-Based secure control for switched systems","authors":"Bin Lu , Lili Li , Jinqi Liu , Xiaowei Zhao","doi":"10.1016/j.jfranklin.2026.108411","DOIUrl":"10.1016/j.jfranklin.2026.108411","url":null,"abstract":"<div><div>Deception attacks in switched systems can manipulate both the switching signal and system state, inducing severe asynchronous switching. While existing research predominantly employs passive mitigation strategies, this paper proposes a proactive secure control framework integrating prediction into attack detection. A model predictive control-based attack detection mechanism, augmented by a mode-state predictor, detects attacks by comparing predicted and received system modes and states. A detection-aware event-triggered mechanism and a mode-based try-once-discard protocol are implemented to reduce asynchrony between the subsystem and the controller. Additionally, an optimal subsystem switching rule, derived from the optimal states, ensures stability and security during switching. Asymptotic stability of the closed-loop system is analytically verified, and its feasibility is validated through an unmanned surface vehicle case study.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108411"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2026-01-08DOI: 10.1016/j.jfranklin.2026.108410
Wei Zhang , Yu Zhang , Tianhao Su , Yao Li
This paper mainly studies the model predictive control problem with probabilistic bit flips under constrained bitrate limitations. Since the bitrate required for data transmission often exceeds the maximum bitrate that the system can provide, the transmitted data needs to be quantized to meet the bitrate requirements. The quantized data is encoded into binary data streams for long-distance transmission. However, due to external interferences such as channel noise, certain bits in the binary data streams may flip between 0 and 1, causing flip errors that affect subsequent control.Therefore, this paper quantizes data into specific intervals through a uniform quantizer and establishes a mathematical model of probabilistic bit flips by incorporating the description of bit probability flips using Bernoulli distributions. By combining it with polyhedral uncertain systems, the impacts of quantization and bit flips are transformed into system uncertainties, which are then uniformly handled in model predictive control. Considering the difficulty of obtaining system states in practical scenarios, a dynamic output feedback control framework under robust model predictive control is proposed. Singular value decomposition technology is used to address the non-convexity in the system, and solvable auxiliary optimization problems are proposed. Additionally, sufficient criteria for the mean-square stability of system states are provided. Finally, the effectiveness of the proposed method is verified through two simulation cases.
{"title":"Robust model predictive control with probabilistic bit flips under constrained bit rate","authors":"Wei Zhang , Yu Zhang , Tianhao Su , Yao Li","doi":"10.1016/j.jfranklin.2026.108410","DOIUrl":"10.1016/j.jfranklin.2026.108410","url":null,"abstract":"<div><div>This paper mainly studies the model predictive control problem with probabilistic bit flips under constrained bitrate limitations. Since the bitrate required for data transmission often exceeds the maximum bitrate that the system can provide, the transmitted data needs to be quantized to meet the bitrate requirements. The quantized data is encoded into binary data streams for long-distance transmission. However, due to external interferences such as channel noise, certain bits in the binary data streams may flip between 0 and 1, causing flip errors that affect subsequent control.Therefore, this paper quantizes data into specific intervals through a uniform quantizer and establishes a mathematical model of probabilistic bit flips by incorporating the description of bit probability flips using Bernoulli distributions. By combining it with polyhedral uncertain systems, the impacts of quantization and bit flips are transformed into system uncertainties, which are then uniformly handled in model predictive control. Considering the difficulty of obtaining system states in practical scenarios, a dynamic output feedback control framework under robust model predictive control is proposed. Singular value decomposition technology is used to address the non-convexity in the system, and solvable auxiliary optimization problems are proposed. Additionally, sufficient criteria for the mean-square stability of system states are provided. Finally, the effectiveness of the proposed method is verified through two simulation cases.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 3","pages":"Article 108410"},"PeriodicalIF":4.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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