Pub Date : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108359
Yuyang Zhao , Dawei Gong , Jiaoyuan Chen , Shijie Song , Minglei Zhu
This study presents a novel data-driven fault-tolerant control (FTC) algorithm for addressing the output containment control problem in multi-agent systems (MASs) with unknown dynamics and actuator faults. To overcome the modeling challenges associated with such systems, a dynamic linearization technique is employed to construct an online model using only real-time input-output data, thereby eliminating the need for prior knowledge of agent dynamics. Building on this framework, an adaptive fault estimator is developed to identify actuator fault information based solely on measurable input-output data. The estimated fault signals are then integrated into the control law to compensate for actuator failures and ensure robust system performance. A rigorous theoretical analysis proves that both the containment error of the MASs and the estimation error of the adaptive fault estimator remain bounded, guaranteeing system stability. Finally, three simulation studies, including two numerical examples and one real-system experiment, are conducted to validate the proposed method, demonstrating its effectiveness, robustness, and practical feasibility.
{"title":"Data-driven output containment fault-tolerant control of unknown multi-agent systems with actuator faults","authors":"Yuyang Zhao , Dawei Gong , Jiaoyuan Chen , Shijie Song , Minglei Zhu","doi":"10.1016/j.jfranklin.2025.108359","DOIUrl":"10.1016/j.jfranklin.2025.108359","url":null,"abstract":"<div><div>This study presents a novel data-driven fault-tolerant control (FTC) algorithm for addressing the output containment control problem in multi-agent systems (MASs) with unknown dynamics and actuator faults. To overcome the modeling challenges associated with such systems, a dynamic linearization technique is employed to construct an online model using only real-time input-output data, thereby eliminating the need for prior knowledge of agent dynamics. Building on this framework, an adaptive fault estimator is developed to identify actuator fault information based solely on measurable input-output data. The estimated fault signals are then integrated into the control law to compensate for actuator failures and ensure robust system performance. A rigorous theoretical analysis proves that both the containment error of the MASs and the estimation error of the adaptive fault estimator remain bounded, guaranteeing system stability. Finally, three simulation studies, including two numerical examples and one real-system experiment, are conducted to validate the proposed method, demonstrating its effectiveness, robustness, and practical feasibility.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108359"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837884","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108320
Huiqin Pei, Hongli Xiao
This paper investigates fault-tolerant group consensus control for hybrid multi-agent systems (HMASs) by event-triggered strategy subject to actuator faults. Firstly, to estimate the states of the agents and the actuator faults, an observer and a fault estimator are constructed using relative output estimation errors, thereby establishing the asymptotic stability of the global estimation error system. Secondly, under the event-triggered strategy, a class of fault-tolerant group consensus protocol for HMASs is proposed to compensate for actuator faults, the grouping coefficient in the protocol is used to distinguish different subgroups of agents. Based on the Lyapunov stability theorem, the stability of the closed-loop system and the convergence of consensus errors are rigorously proved. Furthermore, Zeno behavior is excluded under the proposed triggering strategy. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed event-triggered fault-tolerant protocol.
{"title":"Fault-tolerant group consensus control for hybrid multi-agent systems by observers and event-triggered strategy","authors":"Huiqin Pei, Hongli Xiao","doi":"10.1016/j.jfranklin.2025.108320","DOIUrl":"10.1016/j.jfranklin.2025.108320","url":null,"abstract":"<div><div>This paper investigates fault-tolerant group consensus control for hybrid multi-agent systems (HMASs) by event-triggered strategy subject to actuator faults. Firstly, to estimate the states of the agents and the actuator faults, an observer and a fault estimator are constructed using relative output estimation errors, thereby establishing the asymptotic stability of the global estimation error system. Secondly, under the event-triggered strategy, a class of fault-tolerant group consensus protocol for HMASs is proposed to compensate for actuator faults, the grouping coefficient in the protocol is used to distinguish different subgroups of agents. Based on the Lyapunov stability theorem, the stability of the closed-loop system and the convergence of consensus errors are rigorously proved. Furthermore, Zeno behavior is excluded under the proposed triggering strategy. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed event-triggered fault-tolerant protocol.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108320"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837881","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108347
Hong Liang Cheah, Mohammad Deghat
This paper proposes two formation control laws that reject unknown constant disturbances using only local bearing measurements. The first control law is developed based on finite-time input-to-state stability (FTISS) theory, ensuring that the formation error converges to a neighborhood of zero within a finite time. Then, the formation error converges to zero asymptotically. When there is no disturbance, the formation error converges to zero in finite time. The second control law employs fixed-time input-to-state stability (FXISS) theory, guaranteeing that the formation error converges to a neighborhood of zero within a fixed time, and subsequently converges to zero asymptotically. Unlike existing finite-time bearing-based formation control laws, which typically rely on the availability of a global coordinate frame and some information about the disturbances, our proposed control laws require only local bearing vector measurements. We first examine the case where leaders are stationary and then extend the results to leaders moving with an unknown constant velocity. Furthermore, when disturbances are time-varying, we show that the first control law guarantees FTISS, while the second ensures FXISS. Simulation and experimental results are provided to validate the effectiveness of the proposed control laws.
{"title":"Finite-time and fixed-time formation tracking control with unknown disturbance rejection using only local bearing measurements","authors":"Hong Liang Cheah, Mohammad Deghat","doi":"10.1016/j.jfranklin.2025.108347","DOIUrl":"10.1016/j.jfranklin.2025.108347","url":null,"abstract":"<div><div>This paper proposes two formation control laws that reject unknown constant disturbances using only local bearing measurements. The first control law is developed based on finite-time input-to-state stability (FTISS) theory, ensuring that the formation error converges to a neighborhood of zero within a finite time. Then, the formation error converges to zero asymptotically. When there is no disturbance, the formation error converges to zero in finite time. The second control law employs fixed-time input-to-state stability (FXISS) theory, guaranteeing that the formation error converges to a neighborhood of zero within a fixed time, and subsequently converges to zero asymptotically. Unlike existing finite-time bearing-based formation control laws, which typically rely on the availability of a global coordinate frame and some information about the disturbances, our proposed control laws require only local bearing vector measurements. We first examine the case where leaders are stationary and then extend the results to leaders moving with an unknown constant velocity. Furthermore, when disturbances are time-varying, we show that the first control law guarantees FTISS, while the second ensures FXISS. Simulation and experimental results are provided to validate the effectiveness of the proposed control laws.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108347"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837882","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108321
Ruru Jia , Lihua Li , Xiaoyan Yang , Wei Zhang , Yuan-Hua Ni
This paper addresses the dynamic event-triggered formation control problem of linear multi-agent systems (MASs) with multiplicative measurement noises, the main contributions are the avoidance of infinitely fast execution and the analysis of stochastic stability. First, a novel dynamic edge-based event-triggered mechanism (ETM) is established to schedule the communication among agents such that some unnecessary information transmission can be reduced to achieve better resource efficiency. Especially, the infinitely fast execution behavior (i.e., Zeno behavior) is effectively avoided by enforcing a uniformly fixed positive constant for all the inter-execution times in ETM. Second, a distributed event-triggered formation protocol with multiplicative noises is designed by using only the relative state measurement. Then, the formation control problem under the protocol is converted to a stochastic stability problem. Sufficient conditions for MASs to reach the formation in the mean square and almost sure sense are provided by stabilizing the corresponding stochastic closed-loop system. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.
{"title":"Dynamic event-triggered formation control of linear multi-agent systems with multiplicative noises","authors":"Ruru Jia , Lihua Li , Xiaoyan Yang , Wei Zhang , Yuan-Hua Ni","doi":"10.1016/j.jfranklin.2025.108321","DOIUrl":"10.1016/j.jfranklin.2025.108321","url":null,"abstract":"<div><div>This paper addresses the dynamic event-triggered formation control problem of linear multi-agent systems (MASs) with multiplicative measurement noises, the main contributions are the avoidance of infinitely fast execution and the analysis of stochastic stability. First, a novel dynamic edge-based event-triggered mechanism (ETM) is established to schedule the communication among agents such that some unnecessary information transmission can be reduced to achieve better resource efficiency. Especially, the infinitely fast execution behavior (i.e., Zeno behavior) is effectively avoided by enforcing a uniformly fixed positive constant for all the inter-execution times in ETM. Second, a distributed event-triggered formation protocol with multiplicative noises is designed by using only the relative state measurement. Then, the formation control problem under the protocol is converted to a stochastic stability problem. Sufficient conditions for MASs to reach the formation in the mean square and almost sure sense are provided by stabilizing the corresponding stochastic closed-loop system. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108321"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837952","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108361
Deepak Tripathi , Anuraj Singh , Vijay Pal Bajiya
This study investigates the behavior of a predator-prey interaction with Leslie-type growth and a generalized Holling type-IV functional response, incorporating both linear harvesting of prey and alternative food sources for predators. We first establish the positivity and boundedness of population densities, identifying four equilibrium points: extinction of both species, predator only survival, prey only survival under specific harvesting conditions, and coexistence of both species. The stability of these equilibria is explored, revealing how harvesting and alternative food impact the populations persistence. The key findings include the emergence of saddle-node bifurcation, transcritical bifurcation, and Hopf-bifurcation (codimension-1) as the harvesting parameter is varied, marking critical thresholds where small changes can lead to population oscillations or collapse. Additionally, a Bogdanov-Takens (codimension-2) bifurcation underscores the delicate balance between harvesting and growth rates, emphasizing the fragility of ecosystems. Ecologically, moderate alternative food enhances predator resilience, while excessive alternative food destabilizes the ecosystem. Optimal harvesting strategies are also identified, aiming to maximize economic yield while ensuring long-term ecological balance and species sustainability. To substantiate these analytical conclusions, exhaustive numerical simulations are carried out. Compared to the previous study [1] that primarily explored bifurcation structures without management interventions, the present work integrates prey harvesting and alternative food availability, thereby uncovering new ecological and economic insights into system stability and control. The findings of this study highlight the need for adaptive management strategies that can simultaneously achieve economic gains while maintaining ecological sustainability.
{"title":"Bogdanov-Takens bifurcation and optimal harvesting strategies in species interactions with a generalist predator","authors":"Deepak Tripathi , Anuraj Singh , Vijay Pal Bajiya","doi":"10.1016/j.jfranklin.2025.108361","DOIUrl":"10.1016/j.jfranklin.2025.108361","url":null,"abstract":"<div><div>This study investigates the behavior of a predator-prey interaction with Leslie-type growth and a generalized Holling type-IV functional response, incorporating both linear harvesting of prey and alternative food sources for predators. We first establish the positivity and boundedness of population densities, identifying four equilibrium points: extinction of both species, predator only survival, prey only survival under specific harvesting conditions, and coexistence of both species. The stability of these equilibria is explored, revealing how harvesting and alternative food impact the populations persistence. The key findings include the emergence of saddle-node bifurcation, transcritical bifurcation, and Hopf-bifurcation (codimension-1) as the harvesting parameter is varied, marking critical thresholds where small changes can lead to population oscillations or collapse. Additionally, a Bogdanov-Takens (codimension-2) bifurcation underscores the delicate balance between harvesting and growth rates, emphasizing the fragility of ecosystems. Ecologically, moderate alternative food enhances predator resilience, while excessive alternative food destabilizes the ecosystem. Optimal harvesting strategies are also identified, aiming to maximize economic yield while ensuring long-term ecological balance and species sustainability. To substantiate these analytical conclusions, exhaustive numerical simulations are carried out. Compared to the previous study [1] that primarily explored bifurcation structures without management interventions, the present work integrates prey harvesting and alternative food availability, thereby uncovering new ecological and economic insights into system stability and control. The findings of this study highlight the need for adaptive management strategies that can simultaneously achieve economic gains while maintaining ecological sustainability.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108361"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145881060","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108368
Meiqi Tang , Junjie Fu
Robotic control is increasingly encountering complex environments with uncertain dynamics, posing critical challenges for controller design. Combining data-driven learning methods with adaptive control enhances the control performance in such scenarios. As Bayesian non-parametric models, Gaussian processes (GPs) provide flexibility in data-driven modeling that enhances adaptive control performance, and their principled uncertainty quantification offers explicit support for stability analysis and robust controller design. This paper investigates trajectory tracking of second-order single-input single-output (SISO) affine nonlinear control systems and develops a fully output-driven, safety-guaranteed GP-based robust adaptive tracking control method. To this end, GPs are employed to model unknown dynamics and provide principled uncertainty quantification, which is then leveraged in the proposed robust controller design to ensure probabilistic asymptotic stability. Safety is ensured through a Barrier Lyapunov function, resulting in improved computational efficiency compared with optimization-based methods. Moreover, a novel learning-based predefined-time state observer is incorporated into the controller design. This observer ensures that the system enters the region of strict asymptotic stability within a predictable time, enhancing both safety guarantees and overall convergence performance. The effectiveness of the proposed control strategy is demonstrated through simulation examples.
{"title":"Output-driven robust adaptive trajectory tracking using gaussian processes with safety and stability guarantees","authors":"Meiqi Tang , Junjie Fu","doi":"10.1016/j.jfranklin.2025.108368","DOIUrl":"10.1016/j.jfranklin.2025.108368","url":null,"abstract":"<div><div>Robotic control is increasingly encountering complex environments with uncertain dynamics, posing critical challenges for controller design. Combining data-driven learning methods with adaptive control enhances the control performance in such scenarios. As Bayesian non-parametric models, Gaussian processes (GPs) provide flexibility in data-driven modeling that enhances adaptive control performance, and their principled uncertainty quantification offers explicit support for stability analysis and robust controller design. This paper investigates trajectory tracking of second-order single-input single-output (SISO) affine nonlinear control systems and develops a fully output-driven, safety-guaranteed GP-based robust adaptive tracking control method. To this end, GPs are employed to model unknown dynamics and provide principled uncertainty quantification, which is then leveraged in the proposed robust controller design to ensure probabilistic asymptotic stability. Safety is ensured through a Barrier Lyapunov function, resulting in improved computational efficiency compared with optimization-based methods. Moreover, a novel learning-based predefined-time state observer is incorporated into the controller design. This observer ensures that the system enters the region of strict asymptotic stability within a predictable time, enhancing both safety guarantees and overall convergence performance. The effectiveness of the proposed control strategy is demonstrated through simulation examples.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108368"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145838019","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108341
Xianying Wu , Zhi Liu , Meijian Tan , C. L. Philip Chen
This paper focuses on designing fault-tolerant formation control strategies using adaptive neural networks for nonlinear multi-agent systems experiencing intermittent actuator failures. Due to the presence of unknown nonlinearities and states that cannot be measured in the controlled MASs, neural networks (NNs) serve to model the unknown subsystems, and the output measurements are utilized to develop a state observer. By introducing the first-order filtering technique, problems such as computational explosion in the backstepping method are avoided. Furthermore, combining the prescribed performance control (PPC) method with the sliding mode control (SMC) removes the limitation of tracking error with respect to the initial conditions, and the approximation error can asymptotically approach a bounded set in predetermined time even under the effect of unexpected perturbations. By incorporating the Lyapunov-Barrier function, the proposed control protocol enables followers to avoid collisions in case of actuator failure and ensures that the formation tracking error transitions smoothly and safely to reach a predefined convergence region. Finally, simulations verify the effectiveness achieved by the controller.
{"title":"Distributed adaptive neural fault-tolerant formation control with prescribed performance and collision avoidance for nonlinear multi-agent systems under intermittent actuator failures","authors":"Xianying Wu , Zhi Liu , Meijian Tan , C. L. Philip Chen","doi":"10.1016/j.jfranklin.2025.108341","DOIUrl":"10.1016/j.jfranklin.2025.108341","url":null,"abstract":"<div><div>This paper focuses on designing fault-tolerant formation control strategies using adaptive neural networks for nonlinear multi-agent systems experiencing intermittent actuator failures. Due to the presence of unknown nonlinearities and states that cannot be measured in the controlled MASs, neural networks (NNs) serve to model the unknown subsystems, and the output measurements are utilized to develop a state observer. By introducing the first-order filtering technique, problems such as computational explosion in the backstepping method are avoided. Furthermore, combining the prescribed performance control (PPC) method with the sliding mode control (SMC) removes the limitation of tracking error with respect to the initial conditions, and the approximation error can asymptotically approach a bounded set in predetermined time even under the effect of unexpected perturbations. By incorporating the Lyapunov-Barrier function, the proposed control protocol enables followers to avoid collisions in case of actuator failure and ensures that the formation tracking error transitions smoothly and safely to reach a predefined convergence region. Finally, simulations verify the effectiveness achieved by the controller.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108341"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926857","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 : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108324
Peng Bo , Wanqing Tu , Qingchang Guo , Jianbin Luo
This paper proposes a novel cooperative trajectory-tracking control framework for distributed autonomous marine vehicle (AMV) systems subject to randomly switching network topologies and unknown external disturbances. To accommodate heterogeneous sensing capabilities among AMVs, a layered communication topology is introduced, which characterises the hierarchical leader-follower interactions and captures random variations in inter-agent connectivity. The AMV dynamics considered include nonlinear effects such as Coriolis and centripetal forces, together with velocity-dependent damping. To handle disturbances, a layered disturbance observer is constructed to estimate external inputs in real time, and a robust backstepping-based controller is developed by leveraging the estimated information to achieve accurate trajectory tracking. Rigorous Lyapunov-based analysis is provided, guaranteeing uniform ultimate boundedness of all tracking errors. The effectiveness and robustness of the proposed control scheme are further validated through numerical simulations of a multi-AMV system navigating under stochastic topological variations, demonstrating strong adaptability to realistic marine environments.
{"title":"Robust layered trajectory tracking control for multiple AMVs under unknown disturbances and randomly switching topologies","authors":"Peng Bo , Wanqing Tu , Qingchang Guo , Jianbin Luo","doi":"10.1016/j.jfranklin.2025.108324","DOIUrl":"10.1016/j.jfranklin.2025.108324","url":null,"abstract":"<div><div>This paper proposes a novel cooperative trajectory-tracking control framework for distributed autonomous marine vehicle (AMV) systems subject to randomly switching network topologies and unknown external disturbances. To accommodate heterogeneous sensing capabilities among AMVs, a layered communication topology is introduced, which characterises the hierarchical leader-follower interactions and captures random variations in inter-agent connectivity. The AMV dynamics considered include nonlinear effects such as Coriolis and centripetal forces, together with velocity-dependent damping. To handle disturbances, a layered disturbance observer is constructed to estimate external inputs in real time, and a robust backstepping-based controller is developed by leveraging the estimated information to achieve accurate trajectory tracking. Rigorous Lyapunov-based analysis is provided, guaranteeing uniform ultimate boundedness of all tracking errors. The effectiveness and robustness of the proposed control scheme are further validated through numerical simulations of a multi-AMV system navigating under stochastic topological variations, demonstrating strong adaptability to realistic marine environments.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108324"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145837888","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 : 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":"2025-12-18","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}
Pub Date : 2025-12-18DOI: 10.1016/j.jfranklin.2025.108326
Jing-Wen Yi , Xiao-Ying Cao , Li-Bin Qian , Li Chai
This paper addresses the time-varying formation tracking (TVFT) problem for discrete-time second-order multi-agent systems with a dynamic leader. The acceleration input of the dynamic leader is unknown, and only a subset of followers can access the leader’s states. Firstly, a novel discrete-time PI-like TVFT protocol is designed, incorporating an integral term to eliminate the tracking error. Theoretical analyses demonstrate that the system can asymptotically achieve the desired time-varying formation while concurrently accomplishing error-free tracking. The necessary and sufficient conditions for the TVFT problem are presented. Furthermore, explicit expressions of the fastest convergence rate and the corresponding optimal control gains are provided by solving an optimization problem with ten nonlinear inequality constraints. The results reveal that the fastest convergence rate of the TVFT is solely determined by the connectivity of the topology when the leader’s acceleration input is bounded. Finally, numerical simulations validate the effectiveness of the proposed theoretical results.
{"title":"Optimal design of time-varying formation tracking algorithms for multi-agent systems with an unknown-input dynamic leader","authors":"Jing-Wen Yi , Xiao-Ying Cao , Li-Bin Qian , Li Chai","doi":"10.1016/j.jfranklin.2025.108326","DOIUrl":"10.1016/j.jfranklin.2025.108326","url":null,"abstract":"<div><div>This paper addresses the time-varying formation tracking (TVFT) problem for discrete-time second-order multi-agent systems with a dynamic leader. The acceleration input of the dynamic leader is unknown, and only a subset of followers can access the leader’s states. Firstly, a novel discrete-time <em>PI</em>-like TVFT protocol is designed, incorporating an integral term to eliminate the tracking error. Theoretical analyses demonstrate that the system can asymptotically achieve the desired time-varying formation while concurrently accomplishing error-free tracking. The necessary and sufficient conditions for the TVFT problem are presented. Furthermore, explicit expressions of the fastest convergence rate and the corresponding optimal control gains are provided by solving an optimization problem with ten nonlinear inequality constraints. The results reveal that the fastest convergence rate of the TVFT is solely determined by the connectivity of the topology when the leader’s acceleration input is bounded. Finally, numerical simulations validate the effectiveness of the proposed theoretical results.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"363 2","pages":"Article 108326"},"PeriodicalIF":4.2,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926831","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号