Pub Date : 2025-01-06DOI: 10.1109/TSMC.2024.3519347
Jianghong Zhou;Jun Luo;Huayan Pu;Yi Qin
Aiming at the large differences between tasks in continuous remaining useful life (RUL) prediction and the limited information capturing capability of the existing continuous learning (CL) methods, this article develops a novel multibranch horizontal augmentation network (MBHAN). First, a hierarchical self-attention (HSA) mechanism is proposed to capture the local degradation features and dependencies at different scales and enhance the representation capacity of RUL prediction model. Based on HSA and temporal convolutional network (TCN), a time-frequency fusion TCN (TFFTCN) is designed to mine the hidden degradation information from the time-domain and frequency-domain data. Then, a memory weight constraint (MWC) regularization term is built to control the update of important parameters for pervious tasks during the learning of new task. A horizontal network augmentation rule based on the task similarity and MWC is proposed, including the augmentation of a task branch network for small task difference and the augmentation of a feature extraction backbone network for large task difference. On this basis, the MBHAN is proposed to continuously predict RUL of machinery. Finally, the experimental results on the life-cycle bearing and gear datasets demonstrate that TFFTCN achieve an average accuracy of 93% across both datasets, surpassing the existing prediction methods.
{"title":"Multibranch Horizontal Augmentation Network for Continuous Remaining Useful Life Prediction","authors":"Jianghong Zhou;Jun Luo;Huayan Pu;Yi Qin","doi":"10.1109/TSMC.2024.3519347","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3519347","url":null,"abstract":"Aiming at the large differences between tasks in continuous remaining useful life (RUL) prediction and the limited information capturing capability of the existing continuous learning (CL) methods, this article develops a novel multibranch horizontal augmentation network (MBHAN). First, a hierarchical self-attention (HSA) mechanism is proposed to capture the local degradation features and dependencies at different scales and enhance the representation capacity of RUL prediction model. Based on HSA and temporal convolutional network (TCN), a time-frequency fusion TCN (TFFTCN) is designed to mine the hidden degradation information from the time-domain and frequency-domain data. Then, a memory weight constraint (MWC) regularization term is built to control the update of important parameters for pervious tasks during the learning of new task. A horizontal network augmentation rule based on the task similarity and MWC is proposed, including the augmentation of a task branch network for small task difference and the augmentation of a feature extraction backbone network for large task difference. On this basis, the MBHAN is proposed to continuously predict RUL of machinery. Finally, the experimental results on the life-cycle bearing and gear datasets demonstrate that TFFTCN achieve an average accuracy of 93% across both datasets, surpassing the existing prediction methods.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2237-2249"},"PeriodicalIF":8.6,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438367","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 : 2025-01-06DOI: 10.1109/TSMC.2024.3521369
Tássio M. Linhares;Eduardo S. Tognetti;Taís R. Calliero
This work addresses the problem of designing dynamic output feedback controllers for Takagi-Sugeno (T-S) fuzzy systems subjected to inexact measurements of premise variables. Instead of assuming that the premise variables are precisely available for the controller, this work provides linear matrix inequalities (LMIs) conditions to design controller gains depending on premise variables with additive uncertainties. This uncertainty model includes inexact measurements of the premise variables due to sensor devices or an approximate representation in the T-S modeling, which can assume the form of absolute uncertainties in the membership functions. Numerical examples illustrate the robustness of the approach.
{"title":"Output Feedback Control With Inexact Premise Variables of T-S Fuzzy Systems","authors":"Tássio M. Linhares;Eduardo S. Tognetti;Taís R. Calliero","doi":"10.1109/TSMC.2024.3521369","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3521369","url":null,"abstract":"This work addresses the problem of designing dynamic output feedback controllers for Takagi-Sugeno (T-S) fuzzy systems subjected to inexact measurements of premise variables. Instead of assuming that the premise variables are precisely available for the controller, this work provides linear matrix inequalities (LMIs) conditions to design controller gains depending on premise variables with additive uncertainties. This uncertainty model includes inexact measurements of the premise variables due to sensor devices or an approximate representation in the T-S modeling, which can assume the form of absolute uncertainties in the membership functions. Numerical examples illustrate the robustness of the approach.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2380-2386"},"PeriodicalIF":8.6,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465566","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}
This article proposes a stabilizing control scheme based on partial-state decomposition to exponentially stabilize multi-input and multioutput nonminimum phase nonlinear systems in a general normal form with a general relative degree. The scheme reveals that partial-state variables can play an essential role in stabilizing the whole system. Specifically, partial-state variables are decomposed into a sum of two vector signals s and N. Then, setting s as the output vector, a new normal form is derived. For the new normal form, N and an auxiliary signal are designed to exponentially stabilize the unstable zero/internal dynamics of the auxiliary system; and the real input is designed to ensure that $s $ is exponentially stable. In particular, the zero/internal dynamics dependence on the input is fully considered in this article, and the proposed method ensures global stabilization of the closed-loop system without relying on the existence condition of Lyapunov functions. Finally, a high fidelity hypersonic vehicle model is given to show the design procedure and verify the feasibility and validity of the proposed stabilizing control scheme.
本文提出了一种基于偏态分解的稳定控制方案，以指数方式稳定具有一般相对度的一般正态形式的多输入和多输出非最小相位非线性系统。该方案揭示了偏态变量在稳定整个系统中的重要作用。具体来说，部分状态变量被分解为两个矢量信号 s 和 N 之和。对于新的正态形式，N 和辅助信号的设计是为了指数稳定辅助系统不稳定的零点/内部动态；而实际输入的设计是为了确保 $s $ 是指数稳定的。特别是，本文充分考虑了零点/内部动力学对输入的依赖性，提出的方法无需依赖李亚普诺夫函数的存在条件就能确保闭环系统的全局稳定。最后，文章给出了一个高保真高超音速飞行器模型，以展示设计过程并验证所提稳定控制方案的可行性和有效性。
{"title":"Partial-State Decomposition-Based Control of MIMO Nonminimum Phase Nonlinear Systems With Application to a Hypersonic Vehicle Model","authors":"Xinhao Zhang;Yanjun Zhang;Jianliang Ai;Yeguang Wang;Xuelin Zhang","doi":"10.1109/TSMC.2024.3521380","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3521380","url":null,"abstract":"This article proposes a stabilizing control scheme based on partial-state decomposition to exponentially stabilize multi-input and multioutput nonminimum phase nonlinear systems in a general normal form with a general relative degree. The scheme reveals that partial-state variables can play an essential role in stabilizing the whole system. Specifically, partial-state variables are decomposed into a sum of two vector signals s and N. Then, setting s as the output vector, a new normal form is derived. For the new normal form, N and an auxiliary signal are designed to exponentially stabilize the unstable zero/internal dynamics of the auxiliary system; and the real input is designed to ensure that <inline-formula> <tex-math>$s $ </tex-math></inline-formula> is exponentially stable. In particular, the zero/internal dynamics dependence on the input is fully considered in this article, and the proposed method ensures global stabilization of the closed-loop system without relying on the existence condition of Lyapunov functions. Finally, a high fidelity hypersonic vehicle model is given to show the design procedure and verify the feasibility and validity of the proposed stabilizing control scheme.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2289-2301"},"PeriodicalIF":8.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465576","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 : 2025-01-03DOI: 10.1109/TSMC.2024.3520823
Xiaobing Nie;Boqiang Cao;Wei Xing Zheng;Jinde Cao
This work explores the issue of multistability for a competitive neural network (NN) class with sigmoidal activation functions (AFs) involving state-dependent switching and fractional-order derivative. Specifically, first, we consider three different switching point locations, and establish some sufficient criteria ensuring that NNs with n-neurons can have, and only have, $5^{n_{1}}cdot 3^{n_{2}}$ equilibrium points (EPs) with $n_{1}+n_{2}=n$ , by utilizing the geometric features of the sigmoidal functions, the fixed point theorem, the Filippov’s EP definition, and the contraction mapping theorem. Then, based on novel Lyapunov functions and by applying the fractional-order calculus theory, it is demonstrated that $3^{n_{1}}cdot 2^{n_{2}}$ out of $5^{n_{1}}cdot 3^{n_{2}}$ total EPs are locally stable. This work’s investigation reveals that competitive NNs with switching afford more storage capacity compared to the nonswitching case. Additionally, our results are valid for the integer-order and fractional-order switched NNs, improving and generalizing current works. Furthermore, two numerical examples and an application example of associative memory are provided to validate the effectiveness of the theoretical findings, and the way various fractional orders affect the NNs’ convergence speed is shown through simulations.
{"title":"Multistability Analysis of Fractional-Order State-Dependent Switched Competitive Neural Networks With Sigmoidal Activation Functions","authors":"Xiaobing Nie;Boqiang Cao;Wei Xing Zheng;Jinde Cao","doi":"10.1109/TSMC.2024.3520823","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3520823","url":null,"abstract":"This work explores the issue of multistability for a competitive neural network (NN) class with sigmoidal activation functions (AFs) involving state-dependent switching and fractional-order derivative. Specifically, first, we consider three different switching point locations, and establish some sufficient criteria ensuring that NNs with n-neurons can have, and only have, <inline-formula> <tex-math>$5^{n_{1}}cdot 3^{n_{2}}$ </tex-math></inline-formula> equilibrium points (EPs) with <inline-formula> <tex-math>$n_{1}+n_{2}=n$ </tex-math></inline-formula>, by utilizing the geometric features of the sigmoidal functions, the fixed point theorem, the Filippov’s EP definition, and the contraction mapping theorem. Then, based on novel Lyapunov functions and by applying the fractional-order calculus theory, it is demonstrated that <inline-formula> <tex-math>$3^{n_{1}}cdot 2^{n_{2}}$ </tex-math></inline-formula> out of <inline-formula> <tex-math>$5^{n_{1}}cdot 3^{n_{2}}$ </tex-math></inline-formula> total EPs are locally stable. This work’s investigation reveals that competitive NNs with switching afford more storage capacity compared to the nonswitching case. Additionally, our results are valid for the integer-order and fractional-order switched NNs, improving and generalizing current works. Furthermore, two numerical examples and an application example of associative memory are provided to validate the effectiveness of the theoretical findings, and the way various fractional orders affect the NNs’ convergence speed is shown through simulations.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2106-2119"},"PeriodicalIF":8.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438415","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 : 2025-01-03DOI: 10.1109/TSMC.2024.3522116
Shubo Wang;Chuanbin Sun;Qiang Chen;Haoran He
Robot systems, due to their unique flexibility and economy, are widely used in modern industry and intelligent manufacturing. The parameters of the system are unknown, and traditional parameter estimation methods are difficult to achieve fixed time convergence, which leads to extremely position tracking control problem. In addition, the transient and steady-state performance of the robot system is difficult to specify in advance. In this article, a novel composite learning fixed-time (FxT) control strategy is proposed for the robotic systems to deal with these issues. The funnel control (FC) is utilized to transform the original error system into a new error dynamics with transient performance constraints. The two-phase nonsingular FxT sliding mode surface is constructed to avoid the singularity problem. Then, the filter operation is introduced to obtain the expression of parameter estimation error and is used to design the composite learning law. To achieve parameter estimation, a FxT composite learning law based on online historical data and regression extension is proposed, where the interval excitation (IE) is considered in the adaptive law. Finally, the designed adaption is incorporated into the nonsingular FxT sliding mode control to achieve tracking control. Moreover, the comparison of three different controllers is made to demonstrate the benefits of the developed control strategy.
{"title":"Composite Learning Fixed-Time Control for Nonlinear Servo Systems With State Constraints and Unknown Dynamics","authors":"Shubo Wang;Chuanbin Sun;Qiang Chen;Haoran He","doi":"10.1109/TSMC.2024.3522116","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3522116","url":null,"abstract":"Robot systems, due to their unique flexibility and economy, are widely used in modern industry and intelligent manufacturing. The parameters of the system are unknown, and traditional parameter estimation methods are difficult to achieve fixed time convergence, which leads to extremely position tracking control problem. In addition, the transient and steady-state performance of the robot system is difficult to specify in advance. In this article, a novel composite learning fixed-time (FxT) control strategy is proposed for the robotic systems to deal with these issues. The funnel control (FC) is utilized to transform the original error system into a new error dynamics with transient performance constraints. The two-phase nonsingular FxT sliding mode surface is constructed to avoid the singularity problem. Then, the filter operation is introduced to obtain the expression of parameter estimation error and is used to design the composite learning law. To achieve parameter estimation, a FxT composite learning law based on online historical data and regression extension is proposed, where the interval excitation (IE) is considered in the adaptive law. Finally, the designed adaption is incorporated into the nonsingular FxT sliding mode control to achieve tracking control. Moreover, the comparison of three different controllers is made to demonstrate the benefits of the developed control strategy.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2332-2342"},"PeriodicalIF":8.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465568","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 : 2025-01-03DOI: 10.1109/TSMC.2024.3518513
Rongqiang Tang;Peng Shi;Xinsong Yang;Guanghui Wen;Lei Shi
Considering the memory property of the fractional calculus and the potential diverging state of the open-loop mode, existing analysis methods are difficult to solve the finite-time issue of intermittently controlled fractional-order systems (FOSs). This article studies the finite-time synchronization of coupled FOSs with nonlinearity via fuzzy intermittent quantized control and two novel fractional-order differential inequalities. An interval-type 2 Takagi-Sugeno fuzzy technique is introduced, which not only facilitates the handling of the nonlinear term in the error dynamic system, but also greatly simplifies the control design. Synchronization conditions in form of linear matrix inequalities are provided by designing a novel Lyapunov function on the basis of ellipsoidal norm. Moreover, two corollaries show the generality of the new analysis framework. Compared with existing results, it is amazing that the decreasing magnitude of Lyapunov function on the control intervals can be smaller than its increasing magnitude on the subsequent noncontrol interval. Finally, Chua’s system is used to clarify the effectiveness of theoretical outcomes.
{"title":"Finite-Time Synchronization of Coupled Fractional-Order Systems via Intermittent IT-2 Fuzzy Control","authors":"Rongqiang Tang;Peng Shi;Xinsong Yang;Guanghui Wen;Lei Shi","doi":"10.1109/TSMC.2024.3518513","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3518513","url":null,"abstract":"Considering the memory property of the fractional calculus and the potential diverging state of the open-loop mode, existing analysis methods are difficult to solve the finite-time issue of intermittently controlled fractional-order systems (FOSs). This article studies the finite-time synchronization of coupled FOSs with nonlinearity via fuzzy intermittent quantized control and two novel fractional-order differential inequalities. An interval-type 2 Takagi-Sugeno fuzzy technique is introduced, which not only facilitates the handling of the nonlinear term in the error dynamic system, but also greatly simplifies the control design. Synchronization conditions in form of linear matrix inequalities are provided by designing a novel Lyapunov function on the basis of ellipsoidal norm. Moreover, two corollaries show the generality of the new analysis framework. Compared with existing results, it is amazing that the decreasing magnitude of Lyapunov function on the control intervals can be smaller than its increasing magnitude on the subsequent noncontrol interval. Finally, Chua’s system is used to clarify the effectiveness of theoretical outcomes.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2022-2032"},"PeriodicalIF":8.6,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438388","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 : 2025-01-01DOI: 10.1109/TSMC.2024.3520600
Wenting Song;Yi Zuo;Shaocheng Tong
In this article, a fuzzy optimal event-triggered dynamic positioning control approach with a Q-learning value iteration (VI) algorithm is developed for unmanned surface vehicles (USVs) systems. The USV systems are first modeled by Takagi-Sugeno (T-S) fuzzy systems. To reduce the communication resources and controller update times, an event-triggered mechanism is designed via employing the sampled augmented systems states and triggered control input signals. Based on the developed event-triggered mechanism and Bellman optimality theory, a fuzzy optimal event-triggered control (ETC) approach is presented. Since solution of optimal control policy reduces to algebraic Riccati equations (AREs), its analytical solution is difficult to solve directly. Then, to search its approximation solution, a VI algorithm is formulated. By rigorous proof, the proposed optimal ETC scheme can assure that the USVs systems are asymptotically stable and the Q-learning algorithm is convergent. Finally, the simulation and comparisons results with previous optimal controllers verify the feasibility of the presented optimal ETC scheme.
{"title":"Fuzzy Optimal Event-Triggered Control for Dynamic Positioning of Unmanned Surface Vehicle","authors":"Wenting Song;Yi Zuo;Shaocheng Tong","doi":"10.1109/TSMC.2024.3520600","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3520600","url":null,"abstract":"In this article, a fuzzy optimal event-triggered dynamic positioning control approach with a Q-learning value iteration (VI) algorithm is developed for unmanned surface vehicles (USVs) systems. The USV systems are first modeled by Takagi-Sugeno (T-S) fuzzy systems. To reduce the communication resources and controller update times, an event-triggered mechanism is designed via employing the sampled augmented systems states and triggered control input signals. Based on the developed event-triggered mechanism and Bellman optimality theory, a fuzzy optimal event-triggered control (ETC) approach is presented. Since solution of optimal control policy reduces to algebraic Riccati equations (AREs), its analytical solution is difficult to solve directly. Then, to search its approximation solution, a VI algorithm is formulated. By rigorous proof, the proposed optimal ETC scheme can assure that the USVs systems are asymptotically stable and the Q-learning algorithm is convergent. Finally, the simulation and comparisons results with previous optimal controllers verify the feasibility of the presented optimal ETC scheme.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2302-2311"},"PeriodicalIF":8.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465565","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 : 2025-01-01DOI: 10.1109/TSMC.2024.3520174
Gang Li;Xin Ma;Yibin Li
Tower cranes are complex multi-input multioutput underactuated mechatronics systems. The anti-swing control issue of tower crane with varying suspension cable length and double spherical pendulum effect is still open. Furthermore, the system parameters uncertainty makes it more challenging to implement anti-swing control. In this study, we present an adaptive sliding mode anti-swing control approach based on time-delay estimation for underactuated tower crane with varying suspension cable length and double spherical pendulum effect. First, we employ the Lagrange’s method to develop a seven-degree-of-freedom (7-DOF) tower crane dynamic model that comprehensively accounts for jib slewing, trolley motion, payload hoisting/lowering, and payload/hook spherical swing within a three-dimensional (3-D) space. Then, a sliding mode surface is constructed by analyzing the nonlinear coupling relationship between the unactuated states and actuated states. The time-delay estimation technique with adaptive scheme can adapt and predicate unknown system parameters online. An adaptive sliding mode anti-swing control method with time-delay estimation is designed for 7-DOF tower crane system subject to the parameter uncertainties. The convergence of the closed-loop control system is carefully demonstrated through the Lyapunov stability theory. Finally, the hardware experiments verify the anti-swing control performance and robustness of the designed adaptive sliding mode controller. The superiority of the proposed adaptive sliding mode anti-swing controller is confirmed by a decrease of at least 42.09% and 58.33% in the maximum and residual payload swing, respectively, over state-of-the-art control methods.
{"title":"Adaptive Sliding Mode Control Based on Time-Delay Estimation for Underactuated 7-DOF Tower Crane","authors":"Gang Li;Xin Ma;Yibin Li","doi":"10.1109/TSMC.2024.3520174","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3520174","url":null,"abstract":"Tower cranes are complex multi-input multioutput underactuated mechatronics systems. The anti-swing control issue of tower crane with varying suspension cable length and double spherical pendulum effect is still open. Furthermore, the system parameters uncertainty makes it more challenging to implement anti-swing control. In this study, we present an adaptive sliding mode anti-swing control approach based on time-delay estimation for underactuated tower crane with varying suspension cable length and double spherical pendulum effect. First, we employ the Lagrange’s method to develop a seven-degree-of-freedom (7-DOF) tower crane dynamic model that comprehensively accounts for jib slewing, trolley motion, payload hoisting/lowering, and payload/hook spherical swing within a three-dimensional (3-D) space. Then, a sliding mode surface is constructed by analyzing the nonlinear coupling relationship between the unactuated states and actuated states. The time-delay estimation technique with adaptive scheme can adapt and predicate unknown system parameters online. An adaptive sliding mode anti-swing control method with time-delay estimation is designed for 7-DOF tower crane system subject to the parameter uncertainties. The convergence of the closed-loop control system is carefully demonstrated through the Lyapunov stability theory. Finally, the hardware experiments verify the anti-swing control performance and robustness of the designed adaptive sliding mode controller. The superiority of the proposed adaptive sliding mode anti-swing controller is confirmed by a decrease of at least 42.09% and 58.33% in the maximum and residual payload swing, respectively, over state-of-the-art control methods.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2277-2288"},"PeriodicalIF":8.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465567","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 : 2025-01-01DOI: 10.1109/TSMC.2024.3520135
Chen Wei;Xiaoping Wang;Fangmin Ren;Zhigang Zeng
This article focuses on achieving the finite-time synchronization (FTS) for fractional complex dynamical networks (FCDNs) using hybrid impulsive control. Initially, a novel framework for local FTS is developed, building upon the relaxed inequality ${}_{t_{k}}^{C}D_{t}^{alpha }V(t) le chi V(t) - eta $ . To expand the attraction domain within the local FTS framework, a piecewise fractional-order differential inequality based on impulsive control systems is proposed. Subsequently, a new hybrid control strategy is designed by integrating a simple feedback controller with an impulsive controller involving a finite number of impulses, which can be accurately calculated using the proposed impulsive degree. Additionally, a set of local/global FTS criteria is formulated, and the settling time can be explicitly estimated. Lastly, an illustrative example is presented to demonstrate the effectiveness of the derived results.
本文的重点是利用混合脉冲控制实现分数复杂动力学网络（FCDN）的有限时间同步（FTS）。首先，在松弛不等式 ${}_{t_{k}}^{C}D_{t}^{alpha }V(t) le chi V(t) - eta $ 的基础上，提出了局部 FTS 的新框架。 为了在局部 FTS 框架内扩展吸引域，提出了基于脉冲控制系统的片断分数阶微分不等式。随后，设计了一种新的混合控制策略，将简单反馈控制器与涉及有限脉冲数的脉冲控制器整合在一起，利用提出的脉冲度可以精确计算脉冲数。此外，还制定了一套局部/全局 FTS 准则，并能明确估算出稳定时间。最后，介绍了一个示例来证明推导结果的有效性。
{"title":"Local and Global Finite-Time Synchronization of Fractional-Order Complex Dynamical Networks via Hybrid Impulsive Control","authors":"Chen Wei;Xiaoping Wang;Fangmin Ren;Zhigang Zeng","doi":"10.1109/TSMC.2024.3520135","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3520135","url":null,"abstract":"This article focuses on achieving the finite-time synchronization (FTS) for fractional complex dynamical networks (FCDNs) using hybrid impulsive control. Initially, a novel framework for local FTS is developed, building upon the relaxed inequality <inline-formula> <tex-math>${}_{t_{k}}^{C}D_{t}^{alpha }V(t) le chi V(t) - eta $ </tex-math></inline-formula>. To expand the attraction domain within the local FTS framework, a piecewise fractional-order differential inequality based on impulsive control systems is proposed. Subsequently, a new hybrid control strategy is designed by integrating a simple feedback controller with an impulsive controller involving a finite number of impulses, which can be accurately calculated using the proposed impulsive degree. Additionally, a set of local/global FTS criteria is formulated, and the settling time can be explicitly estimated. Lastly, an illustrative example is presented to demonstrate the effectiveness of the derived results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 3","pages":"2312-2321"},"PeriodicalIF":8.6,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465564","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 : 2025-01-01DOI: 10.1109/TSMC.2024.3520320
Yong Wang;Haojie Jin;Gai-Ge Wang;Ling Wang
Peak carbon emissions and carbon neutrality have become important initiatives for the country to solve outstanding problems of resource and environmental constraints and promote green and low-energy development, and have attracted widespread attention from the industry. The distributed flow shop scheduling problem (DPFSP) is a typical problem that mainly works by consuming energy. However, DPFSP rarely considers energy efficiency and blocking constraints. In this study, an excellent bi-population cooperative discrete differential evolution (BCDDE) is proposed, aiming to address the energy-efficient distributed blocking flow shop scheduling problem (EEDBFSP) with total energy consumption (TEC) and total tardiness (TTD) as two objectives. A bi-population cooperative strategy is constructed to enhance the diversity of BCDDE, while utilizing it to initialize the population to enhance the quality of the initial solution. An adaptive local search operator strategy is developed to improve the BCDDE convergence. Critical and noncritical paths are devised to further optimize TEC and TTD objectives. The efficiency of each strategy related to BCDDE is verified and compared with state-of-the-art algorithms in the benchmark suite. Numerical results show that BCDDE becomes an efficient optimizer for the EEDBFSP, significantly outperforming the state-of-the-art algorithms at the 95% confidence interval.
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