Pub Date : 2025-10-06DOI: 10.1109/TSMC.2025.3613350
Man Gao;Qinghua Zhang;Fan Zhao;Qin Xie;Guoyin Wang;Weiping Ding
The shadowed set, as a three-way approximation model for a fuzzy set, has been extensively studied in model construction, theoretical analysis, data analysis, and applications. However, the current research on the construction of a shadowed set is all based on a single attribute to complete the approximate partition of a simple target concept, i.e., single-granularity-layer space. Multiple attributes are not considered comprehensively to achieve an approximate partition of the complex target concept, i.e., multigranularity-layer space. In addition, the current evaluation criteria of the shadowed set are all reasonable explanations for model construction and threshold determination, lacking an effective evaluation of approximate partition results. Therefore, the multigranularity-layer shadowed set (MGLSS) is proposed in this article, which aims to extend the construction of the shadowed set from single-granularity-layer space to multigranularity-layer space. First, MGLSS is analyzed based on information systems and divided into two models: optimistic-MGLSS (OPT-MGLSS) and pessimistic-MGLSS (PES-MGLSS). Second, the expression form, threshold selection, semantic interpretation, partition rules, basic mathematical theorems, and the definition of fusion operators of MGLSS are analyzed and discussed. Third, two evaluation criteria of coverage and accuracy of approximate partition results are proposed. Finally, six cases are analyzed to illustrate the application scenarios of MGLSS, and one instance and algorithm analysis are given to demonstrate the construction steps, and through the real datasets experiment and statistical hypothesis testing analysis, to provide an objective and quantitative scientific basis for the research conclusion. The experimental results demonstrate the validity and rationality of the MGLSS construction mechanism.
{"title":"Multigranularity-Layer Shadowed Set: A Three-Way Approximation Framework for Fuzzy Information","authors":"Man Gao;Qinghua Zhang;Fan Zhao;Qin Xie;Guoyin Wang;Weiping Ding","doi":"10.1109/TSMC.2025.3613350","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3613350","url":null,"abstract":"The shadowed set, as a three-way approximation model for a fuzzy set, has been extensively studied in model construction, theoretical analysis, data analysis, and applications. However, the current research on the construction of a shadowed set is all based on a single attribute to complete the approximate partition of a simple target concept, i.e., single-granularity-layer space. Multiple attributes are not considered comprehensively to achieve an approximate partition of the complex target concept, i.e., multigranularity-layer space. In addition, the current evaluation criteria of the shadowed set are all reasonable explanations for model construction and threshold determination, lacking an effective evaluation of approximate partition results. Therefore, the multigranularity-layer shadowed set (MGLSS) is proposed in this article, which aims to extend the construction of the shadowed set from single-granularity-layer space to multigranularity-layer space. First, MGLSS is analyzed based on information systems and divided into two models: optimistic-MGLSS (OPT-MGLSS) and pessimistic-MGLSS (PES-MGLSS). Second, the expression form, threshold selection, semantic interpretation, partition rules, basic mathematical theorems, and the definition of fusion operators of MGLSS are analyzed and discussed. Third, two evaluation criteria of coverage and accuracy of approximate partition results are proposed. Finally, six cases are analyzed to illustrate the application scenarios of MGLSS, and one instance and algorithm analysis are given to demonstrate the construction steps, and through the real datasets experiment and statistical hypothesis testing analysis, to provide an objective and quantitative scientific basis for the research conclusion. The experimental results demonstrate the validity and rationality of the MGLSS construction mechanism.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9201-9215"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-06DOI: 10.1109/TSMC.2025.3614997
Xinwei Cao;Yiguo Yang;Shuai Li;Vasilios N. Katsikis
The $k$ -winner-takes-all ($k$ -WTA) problem involves selecting the top $k$ agents with the highest inputs from a set of $n$ candidates. This problem plays a fundamental role in modeling competitive behaviors in social systems and economic environments. In this article, we propose a structurally simplified dynamic neural network to solve the $k$ -WTA problem efficiently. The original $k$ -WTA task is first reformulated as a constrained quadratic programming (QP) problem. A smooth sigmoid function is then introduced to encode inequality constraints implicitly, simplifying the representation. Based on this formulation, we develop a continuous-time neural dynamic model capable of solving the problem in real time. The proposed model is theoretically proven to achieve global convergence and optimality with respect to the $k$ -WTA solution. Extensive numerical experiments, including tests on real-world data, validate the effectiveness of the proposed approach, demonstrating fast convergence, robustness, and practical applicability.
{"title":"k-Winner-Take-All Competition Based on Novel Dynamic Neural Networks","authors":"Xinwei Cao;Yiguo Yang;Shuai Li;Vasilios N. Katsikis","doi":"10.1109/TSMC.2025.3614997","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3614997","url":null,"abstract":"The <inline-formula> <tex-math>$k$ </tex-math></inline-formula>-winner-takes-all (<inline-formula> <tex-math>$k$ </tex-math></inline-formula>-WTA) problem involves selecting the top <inline-formula> <tex-math>$k$ </tex-math></inline-formula> agents with the highest inputs from a set of <inline-formula> <tex-math>$n$ </tex-math></inline-formula> candidates. This problem plays a fundamental role in modeling competitive behaviors in social systems and economic environments. In this article, we propose a structurally simplified dynamic neural network to solve the <inline-formula> <tex-math>$k$ </tex-math></inline-formula>-WTA problem efficiently. The original <inline-formula> <tex-math>$k$ </tex-math></inline-formula>-WTA task is first reformulated as a constrained quadratic programming (QP) problem. A smooth sigmoid function is then introduced to encode inequality constraints implicitly, simplifying the representation. Based on this formulation, we develop a continuous-time neural dynamic model capable of solving the problem in real time. The proposed model is theoretically proven to achieve global convergence and optimality with respect to the <inline-formula> <tex-math>$k$ </tex-math></inline-formula>-WTA solution. Extensive numerical experiments, including tests on real-world data, validate the effectiveness of the proposed approach, demonstrating fast convergence, robustness, and practical applicability.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9255-9265"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-06DOI: 10.1109/TSMC.2025.3614342
Yifan Luo;Xiaomei Wang;Kai Zhao;Ben Niu
In this article, we propose an event-triggered unified fault-tolerant control strategy for continuum robots with prescribed performance, considering multiple levels of actuator failures. First, by integrating a Kelvin–Voigt model, this article introduces an improved constant curvature model for continuum robots accounting for dissipative effects. Second, a comprehensive fault-handling framework is established, which combines extreme fault detection, dynamic actuator redundancy, and asymmetric performance recovery within the context of a unified prescribed performance. Third, by taking advantage of the dynamic characteristic of auxiliary variable and designing suitable event-triggering conditions, a dual-channel event-triggering mechanism is introduced to effectively reduce the number of triggers and optimize the utilization of communication resources. The proposed unified fault-tolerant control strategy ensures the boundedness of all signals in the closed-loop system and multiple kinds of prescribed performance behaviors under actuator failures. Simulation results validate the effectiveness of the proposed control strategy.
{"title":"Event-Triggered Unified Prescribed Performance Control for Continuum Robots With Actuator Faults","authors":"Yifan Luo;Xiaomei Wang;Kai Zhao;Ben Niu","doi":"10.1109/TSMC.2025.3614342","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3614342","url":null,"abstract":"In this article, we propose an event-triggered unified fault-tolerant control strategy for continuum robots with prescribed performance, considering multiple levels of actuator failures. First, by integrating a Kelvin–Voigt model, this article introduces an improved constant curvature model for continuum robots accounting for dissipative effects. Second, a comprehensive fault-handling framework is established, which combines extreme fault detection, dynamic actuator redundancy, and asymmetric performance recovery within the context of a unified prescribed performance. Third, by taking advantage of the dynamic characteristic of auxiliary variable and designing suitable event-triggering conditions, a dual-channel event-triggering mechanism is introduced to effectively reduce the number of triggers and optimize the utilization of communication resources. The proposed unified fault-tolerant control strategy ensures the boundedness of all signals in the closed-loop system and multiple kinds of prescribed performance behaviors under actuator failures. Simulation results validate the effectiveness of the proposed control strategy.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9175-9185"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-06DOI: 10.1109/TSMC.2025.3614905
Chen Ding;Li Ma;Shihong Ding;Xinghuo Yu;Keqi Mei
In this article, a novel adaptive second-order sliding mode (ASOSM) control law is constructed for a general category of sliding mode control (SMC) systems with mismatched uncertainties, including a nonvanishing external disturbance. This innovative control design proposal is accomplished through three key mechanisms. First, the new sliding mode dynamics subject to mismatched uncertainties is derived by selecting the appropriate sliding variables, which can significantly increase the uncertainties existing in the control input channel and relax the strict requirement on the relative degree assumption of the sliding variable. Second, a novel ASOSM controller, which contains some adaptive parameters generated via a three-layer nested adaptive mechanism, is constructed by utilizing the modified adding power integrator (API) approach and the adaptive control technique. Third, the practical finite-time stability of the closed-loop sliding mode system is confirmed by means of the systematic Lyapunov stability theory. The technical advancement of the developed adaptive control scheme lies in its ability to effectively deal with a more general sliding mode dynamics containing multiple uncertainties and guarantee that the practical second-order sliding mode (SOSM) is established in a finite time. Finally, simulation results, incorporating a practical application case, are provided to illustrate the effectiveness of the designed adaptive control scheme.
{"title":"Adaptive Second-Order Sliding Mode Controller Design Subject to Mismatched Uncertainties","authors":"Chen Ding;Li Ma;Shihong Ding;Xinghuo Yu;Keqi Mei","doi":"10.1109/TSMC.2025.3614905","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3614905","url":null,"abstract":"In this article, a novel adaptive second-order sliding mode (ASOSM) control law is constructed for a general category of sliding mode control (SMC) systems with mismatched uncertainties, including a nonvanishing external disturbance. This innovative control design proposal is accomplished through three key mechanisms. First, the new sliding mode dynamics subject to mismatched uncertainties is derived by selecting the appropriate sliding variables, which can significantly increase the uncertainties existing in the control input channel and relax the strict requirement on the relative degree assumption of the sliding variable. Second, a novel ASOSM controller, which contains some adaptive parameters generated via a three-layer nested adaptive mechanism, is constructed by utilizing the modified adding power integrator (API) approach and the adaptive control technique. Third, the practical finite-time stability of the closed-loop sliding mode system is confirmed by means of the systematic Lyapunov stability theory. The technical advancement of the developed adaptive control scheme lies in its ability to effectively deal with a more general sliding mode dynamics containing multiple uncertainties and guarantee that the practical second-order sliding mode (SOSM) is established in a finite time. Finally, simulation results, incorporating a practical application case, are provided to illustrate the effectiveness of the designed adaptive control scheme.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9151-9164"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-06DOI: 10.1109/TSMC.2025.3614831
Zhihang Yu;Bo Wang;Libo Zhang;Zhi Wang;Haibin Zhu
Role-based collaboration (RBC) is an emerging and advanced methodology for problem-solving. A critical aspect of RBC theory is agent evaluation, which aims to assess agents’ abilities through a qualification value derived from a comprehensive analysis of their characteristics. This evaluation directly impacts the quality of role assignments. Existing research typically assumes that the qualification value is either predetermined, based on multiscale criteria, or following a predefined distribution. These assumptions, however, are overly idealistic and difficult to generalize, failing to capture the inherent volatility of the qualification value. To address this challenge, this article introduces a Wasserstein-based ambiguity set to model potential fluctuations in the qualification value, drawing on empirical distributions derived from historical sample data. Building upon the RBC framework and its abstract model environments, classes, agents, roles, groups, and objects (E-CARGO), we propose two data-driven models: distributionally robust group role assignment (DRGRA) and group multirole assignment (DRGMRA). These models aim to achieve more robust and optimal role assignments under uncertainty in agent evaluation. Leveraging strong duality, we reformulate DRGRA and DRGMRA as tractable finite mixed 0–1 convex problems, providing an approximation framework that reduces computational complexity. Notably, these models are adaptable to other problems with no uncertainty in agent evaluation, highlighting their modeling scalability. Experimental results demonstrate the effectiveness and robustness of the proposed models.
{"title":"Role Assignment for Agent Evaluation Under Uncertainty: A Distributionally Robust Approach","authors":"Zhihang Yu;Bo Wang;Libo Zhang;Zhi Wang;Haibin Zhu","doi":"10.1109/TSMC.2025.3614831","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3614831","url":null,"abstract":"Role-based collaboration (RBC) is an emerging and advanced methodology for problem-solving. A critical aspect of RBC theory is agent evaluation, which aims to assess agents’ abilities through a qualification value derived from a comprehensive analysis of their characteristics. This evaluation directly impacts the quality of role assignments. Existing research typically assumes that the qualification value is either predetermined, based on multiscale criteria, or following a predefined distribution. These assumptions, however, are overly idealistic and difficult to generalize, failing to capture the inherent volatility of the qualification value. To address this challenge, this article introduces a Wasserstein-based ambiguity set to model potential fluctuations in the qualification value, drawing on empirical distributions derived from historical sample data. Building upon the RBC framework and its abstract model environments, classes, agents, roles, groups, and objects (E-CARGO), we propose two data-driven models: distributionally robust group role assignment (DRGRA) and group multirole assignment (DRGMRA). These models aim to achieve more robust and optimal role assignments under uncertainty in agent evaluation. Leveraging strong duality, we reformulate DRGRA and DRGMRA as tractable finite mixed 0–1 convex problems, providing an approximation framework that reduces computational complexity. Notably, these models are adaptable to other problems with no uncertainty in agent evaluation, highlighting their modeling scalability. Experimental results demonstrate the effectiveness and robustness of the proposed models.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9280-9294"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-06DOI: 10.1109/TSMC.2025.3612414
Zhaowu Ping;Hui Song;Zhiyong Chen
This article investigates the global robust output regulation of a class of multi-input multi-output (MIMO) time-varying (TV) nonlinear systems with a TV exosystem. Existing linear or nonlinear internal model designs are inadequate for the output regulation problem in TV situations. Therefore, we first transform this control problem into a global robust stabilization problem (GRSP) for a more complex MIMO TV augmented nonlinear system by constructing a TV internal model. Under a series of standard assumptions, this system can be globally stabilized by a recursive state feedback controller. Finally, the proposed algorithm is applied to the disturbance rejection problem of a permanent magnet synchronous motor (PMSM) position servo system, and the experimental results demonstrate its effectiveness.
{"title":"Global Robust Output Regulation of a Class of MIMO Time-Varying Nonlinear Systems and Its Application to PMSM","authors":"Zhaowu Ping;Hui Song;Zhiyong Chen","doi":"10.1109/TSMC.2025.3612414","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3612414","url":null,"abstract":"This article investigates the global robust output regulation of a class of multi-input multi-output (MIMO) time-varying (TV) nonlinear systems with a TV exosystem. Existing linear or nonlinear internal model designs are inadequate for the output regulation problem in TV situations. Therefore, we first transform this control problem into a global robust stabilization problem (GRSP) for a more complex MIMO TV augmented nonlinear system by constructing a TV internal model. Under a series of standard assumptions, this system can be globally stabilized by a recursive state feedback controller. Finally, the proposed algorithm is applied to the disturbance rejection problem of a permanent magnet synchronous motor (PMSM) position servo system, and the experimental results demonstrate its effectiveness.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9141-9150"},"PeriodicalIF":8.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-03DOI: 10.1109/TSMC.2025.3614232
Wenjing Hou;Li Liang;Youqing Wang
This article explores the issue of fault-tolerant optimal pursuit strategies in a nonlinear pursuit-evasion (PE) game involving multiple pursuers and a single evader. The main challenge lies in ensuring the successful capture of the evader despite the presence of actuator partial loss of effectiveness and bias faults within the pursuers group. To overcome this challenge, a two-layer control architecture is proposed. At the control layer, an integral sliding-mode controller is developed to mitigate the impact of bias faults, and an adaptive estimation mechanism is incorporated to identify the fault parameters. At the decision-making layer, performance index functions for both the pursuers and the evader are formulated based on the PE state error and their respective control strategies, and optimal pursuit and evasion strategies are derived by solving the associated Hamilton–Jacobi–Isaacs (HJI) equations. Furthermore, adaptive dynamic programming (ADP) is employed, with each participant using a critic network to approximate the optimal strategies for the pursuers and the evader. The proposed control mechanism is theoretically proven to ensure that all closed-loop signals remain uniformly ultimately bounded, allowing the faulty pursuers to successfully capture the evader. Finally, the effectiveness of the approach is validated through two simulation examples.
{"title":"Fault-Tolerant Control of Nonlinear Multiplayer Pursuit-Evasion Game With Actuator Faults","authors":"Wenjing Hou;Li Liang;Youqing Wang","doi":"10.1109/TSMC.2025.3614232","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3614232","url":null,"abstract":"This article explores the issue of fault-tolerant optimal pursuit strategies in a nonlinear pursuit-evasion (PE) game involving multiple pursuers and a single evader. The main challenge lies in ensuring the successful capture of the evader despite the presence of actuator partial loss of effectiveness and bias faults within the pursuers group. To overcome this challenge, a two-layer control architecture is proposed. At the control layer, an integral sliding-mode controller is developed to mitigate the impact of bias faults, and an adaptive estimation mechanism is incorporated to identify the fault parameters. At the decision-making layer, performance index functions for both the pursuers and the evader are formulated based on the PE state error and their respective control strategies, and optimal pursuit and evasion strategies are derived by solving the associated Hamilton–Jacobi–Isaacs (HJI) equations. Furthermore, adaptive dynamic programming (ADP) is employed, with each participant using a critic network to approximate the optimal strategies for the pursuers and the evader. The proposed control mechanism is theoretically proven to ensure that all closed-loop signals remain uniformly ultimately bounded, allowing the faulty pursuers to successfully capture the evader. Finally, the effectiveness of the approach is validated through two simulation examples.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9069-9083"},"PeriodicalIF":8.7,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-03DOI: 10.1109/TSMC.2025.3613064
Wojciech Przemysław Hunek;Dariusz Paczko
A new nonlinear algorithm covering the inverse model control (IMC) methodology is presented in this article. The perfect control procedure is devoted to the multivariable systems defined in the discrete-time state-space domain. Following the recently introduced perfect control-originated approaches employing the linear continuous- and discrete-time plants of different domains, the new nonlinear instance of such control strategy is proposed here. The innovative scenario follows the behaviors characteristic for its predecessors, in particular in terms of maximum-speed and maximum-accuracy properties. It should be emphasized that the new solution is more general than the existing linear ones, providing the complex original peculiarities. The numerical examples clearly confirm the correctness of the proposed methodology and discuss the key control stability requirement.
{"title":"Perfect Control for Nonlinear Time-Invariant MIMO Systems Described in the Discrete-Time State-Space Framework","authors":"Wojciech Przemysław Hunek;Dariusz Paczko","doi":"10.1109/TSMC.2025.3613064","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3613064","url":null,"abstract":"A new nonlinear algorithm covering the inverse model control (IMC) methodology is presented in this article. The perfect control procedure is devoted to the multivariable systems defined in the discrete-time state-space domain. Following the recently introduced perfect control-originated approaches employing the linear continuous- and discrete-time plants of different domains, the new nonlinear instance of such control strategy is proposed here. The innovative scenario follows the behaviors characteristic for its predecessors, in particular in terms of maximum-speed and maximum-accuracy properties. It should be emphasized that the new solution is more general than the existing linear ones, providing the complex original peculiarities. The numerical examples clearly confirm the correctness of the proposed methodology and discuss the key control stability requirement.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9133-9140"},"PeriodicalIF":8.7,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11192235","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1109/TSMC.2025.3613727
Dachao Li;Kaizhou Gao;Peiyong Duan;Ponnuthurai N. Suganthan;Naiqi Wu
In response to escalating market demands, we extend the distributed assembly flowshop problems (DAFSPs) by incorporating batch delivery, optimizing both total energy consumption (TEC) and total completion time, simultaneously. First, a mathematical model for DAFSP with batch delivery is constructed. Second, the artificial bee colony (ABC) algorithm is enhanced to solve the concerned problems. Two dispatch rules are designed to enhance the quality and diversity of initial solutions. Third, seven local search operators tailored to problem characteristics and two objective-oriented machine speed adjustment strategies are designed for improving the performance of ABC. Two reinforcement learning (RL) algorithms, SARSA and $Q$ -learning, are used to select the appropriate local search operators and speed adjustment strategies during iterations. Two pairs of state-action strategies are developed for local search selection and speed adjustment, respectively. Finally, extensive simulation experiments and detailed analysis demonstrate that the SARSA-assisted ABC has a better performance than its peers for DAFSP with batch delivery.
{"title":"Reinforcement Learning Assisting Artificial Bee Colony Algorithm for Scheduling Distributed Assembly Flowshops With Batch Delivery","authors":"Dachao Li;Kaizhou Gao;Peiyong Duan;Ponnuthurai N. Suganthan;Naiqi Wu","doi":"10.1109/TSMC.2025.3613727","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3613727","url":null,"abstract":"In response to escalating market demands, we extend the distributed assembly flowshop problems (DAFSPs) by incorporating batch delivery, optimizing both total energy consumption (TEC) and total completion time, simultaneously. First, a mathematical model for DAFSP with batch delivery is constructed. Second, the artificial bee colony (ABC) algorithm is enhanced to solve the concerned problems. Two dispatch rules are designed to enhance the quality and diversity of initial solutions. Third, seven local search operators tailored to problem characteristics and two objective-oriented machine speed adjustment strategies are designed for improving the performance of ABC. Two reinforcement learning (RL) algorithms, SARSA and <inline-formula> <tex-math>$Q$ </tex-math></inline-formula>-learning, are used to select the appropriate local search operators and speed adjustment strategies during iterations. Two pairs of state-action strategies are developed for local search selection and speed adjustment, respectively. Finally, extensive simulation experiments and detailed analysis demonstrate that the SARSA-assisted ABC has a better performance than its peers for DAFSP with batch delivery.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9295-9308"},"PeriodicalIF":8.7,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-10-01DOI: 10.1109/TSMC.2025.3613580
Junyan Li;Hesuan Hu
This article concentrates on maximally permissive robustness analysis for automated manufacturing systems (AMSs) that allow multiple server failures in the paradigm of Petri nets (PNs). First, we fully describe resource failures in a more general perspective, formalized as generalized dangerous transitions, and develop an algorithm for computing the set of these transitions. The presence of such transitions results in all subnet systems being divided into two types: dangerous subnet systems and nondangerous subnet systems. Second, based on the number of nondangerous subnets consistently operated, the more general definitions of strongly robust, weakly robust, and nonrobust markings are established. Third, generalized reduced reachability graphs (R2Gs) are constructed to provide a formal tool for robustness analysis. An algorithm is formulated to compute the maximum nondangerous elementary circuits (NDE circuits) for each marking in generalized R2G. Subsequently, by analyzing the transitions involved in the maximum NDE circuits, we derived the necessary and sufficient conditions for identifying the robustness of markings. Finally, examples are provided to demonstrate the proposed methods and illustrate their advantages over existing approaches.
{"title":"Robustness Analysis in Automated Manufacturing Systems Allowing Multiple Server Failures Using Generalized Reduced Reachability Graphs","authors":"Junyan Li;Hesuan Hu","doi":"10.1109/TSMC.2025.3613580","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3613580","url":null,"abstract":"This article concentrates on maximally permissive robustness analysis for automated manufacturing systems (AMSs) that allow multiple server failures in the paradigm of Petri nets (PNs). First, we fully describe resource failures in a more general perspective, formalized as generalized dangerous transitions, and develop an algorithm for computing the set of these transitions. The presence of such transitions results in all subnet systems being divided into two types: dangerous subnet systems and nondangerous subnet systems. Second, based on the number of nondangerous subnets consistently operated, the more general definitions of strongly robust, weakly robust, and nonrobust markings are established. Third, generalized reduced reachability graphs (R2Gs) are constructed to provide a formal tool for robustness analysis. An algorithm is formulated to compute the maximum nondangerous elementary circuits (NDE circuits) for each marking in generalized R2G. Subsequently, by analyzing the transitions involved in the maximum NDE circuits, we derived the necessary and sufficient conditions for identifying the robustness of markings. Finally, examples are provided to demonstrate the proposed methods and illustrate their advantages over existing approaches.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 12","pages":"9216-9229"},"PeriodicalIF":8.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145546977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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