Pub Date : 2024-12-03DOI: 10.1109/TSMC.2024.3504843
Luyao Wen;Ben Niu;Ding Wang;Yuqiang Jiang;Chao Liu;Huanqing Wang
This article mainly considers the adaptive secure bipartite consensus tracking control (BCTC) problem for nonlinear multiagent systems (MASs) under false data injection (FDI) attacks with predefined accuracy. Since FDI attacks produce unknown attack gains, which increases the difficulty of the controller design, an adaptive secure control strategy is given based on the essential property of Nussbaum functions. By improving the traditional coordinate transformation in the current literatures that can only achieve unilateral consensus control, a backstepping-based control algorithm is put forward attaining bilateral consensus control. In addition, the appropriate Lyapunov functions are generated by a class of non-negative functions to construct the adaptive secure bipartite consensus controllers, which not only makes certain that the bilateral errors ultimately converge to a predefined interval, but also guarantees that all the closed-loop signals within the investigated system are bounded. Conclusively, a practical example is provided to validate the effectiveness of the proposed control strategy.
{"title":"Adaptive Secure Bipartite Consensus Tracking Control for Nonlinear Multiagent Systems Under FDI Attacks With Predefined Accuracy","authors":"Luyao Wen;Ben Niu;Ding Wang;Yuqiang Jiang;Chao Liu;Huanqing Wang","doi":"10.1109/TSMC.2024.3504843","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3504843","url":null,"abstract":"This article mainly considers the adaptive secure bipartite consensus tracking control (BCTC) problem for nonlinear multiagent systems (MASs) under false data injection (FDI) attacks with predefined accuracy. Since FDI attacks produce unknown attack gains, which increases the difficulty of the controller design, an adaptive secure control strategy is given based on the essential property of Nussbaum functions. By improving the traditional coordinate transformation in the current literatures that can only achieve unilateral consensus control, a backstepping-based control algorithm is put forward attaining bilateral consensus control. In addition, the appropriate Lyapunov functions are generated by a class of non-negative functions to construct the adaptive secure bipartite consensus controllers, which not only makes certain that the bilateral errors ultimately converge to a predefined interval, but also guarantees that all the closed-loop signals within the investigated system are bounded. Conclusively, a practical example is provided to validate the effectiveness of the proposed control strategy.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1516-1525"},"PeriodicalIF":8.6,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993471","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 : 2024-12-03DOI: 10.1109/TSMC.2024.3495833
Meng Yao;Guoliang Wei;Derui Ding;Yamei Ju
This article mainly considers the networked reset proportional-integral (PI) control issue for a class of cyber physical systems subject to malicious denial-of-service (DoS) attacks and bounded disturbances. Sensor measurement signals are encoded into symbols, and transmitted through the shared communication channel, which has bit rate constraints while susceptible to malicious DoS attacks. In this context, the final closed-loop system is modeled as a hybrid one, which better emphasizes the characteristics of the discussed networked phenomena and reset mechanisms. Then, with the help of the constructed comparison system, a bit rate constrained condition is obtained to ensure that the decoding error is bounded. Subsequently, a series of sufficient conditions are proposed to provide the exponential boundedness of the closed-loop system. Finally, a numerical simulation is presented to validate the effectiveness of the proposed theoretical results.
{"title":"Reset PI Controller Design of Cyber-Physical Systems Under Constrained Bit Rate and DoS Attacks: A Hybrid System Framework","authors":"Meng Yao;Guoliang Wei;Derui Ding;Yamei Ju","doi":"10.1109/TSMC.2024.3495833","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3495833","url":null,"abstract":"This article mainly considers the networked reset proportional-integral (PI) control issue for a class of cyber physical systems subject to malicious denial-of-service (DoS) attacks and bounded disturbances. Sensor measurement signals are encoded into symbols, and transmitted through the shared communication channel, which has bit rate constraints while susceptible to malicious DoS attacks. In this context, the final closed-loop system is modeled as a hybrid one, which better emphasizes the characteristics of the discussed networked phenomena and reset mechanisms. Then, with the help of the constructed comparison system, a bit rate constrained condition is obtained to ensure that the decoding error is bounded. Subsequently, a series of sufficient conditions are proposed to provide the exponential boundedness of the closed-loop system. Finally, a numerical simulation is presented to validate the effectiveness of the proposed theoretical results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1298-1308"},"PeriodicalIF":8.6,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993489","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 : 2024-12-03DOI: 10.1109/TSMC.2024.3498906
Wei Qian;Yanmin Wu;Junqi Yang
This article presents the finite-frequency optimization fault detection (FD) strategy for Takagi-Sugeno (T-S) fuzzy systems. Under the imperfect premise matching (IPM) policy, a weighted fuzzy FD observer (WFFDO) with the $L_{infty }/L_{2}$ robustness performance and the finite-frequency $ H_{-}$ fault sensitivity performance is first proposed, which signifies the residual signal is robust to the external interference and sensitive to potential faults. Some parameters and slack matrices are introduced to obtain more relaxed conditions of designing the WFFDO with mixed performance. Afterward, a new online membership functions (MFs) iterative learning algorithm with the exponential decay learning rate is proposed for the sake of updating the observer MFs in real-time such that optimal $L_{infty }/L_{2}$ performance can be achieved in this article. In addition, sufficient criterion is established so as to ensure the convergence of the structured mean squared error cost function by means of Lyapunov stability theory. Eventually, two simulation examples are given for illustrating the feasibility and superiority of the developed optimization FD technique.
{"title":"A Novel Finite-Frequency Optimization Fault Detection for Fuzzy Systems by Membership Functions Iterative Learning","authors":"Wei Qian;Yanmin Wu;Junqi Yang","doi":"10.1109/TSMC.2024.3498906","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3498906","url":null,"abstract":"This article presents the finite-frequency optimization fault detection (FD) strategy for Takagi-Sugeno (T-S) fuzzy systems. Under the imperfect premise matching (IPM) policy, a weighted fuzzy FD observer (WFFDO) with the <inline-formula> <tex-math>$L_{infty }/L_{2}$ </tex-math></inline-formula> robustness performance and the finite-frequency <inline-formula> <tex-math>$ H_{-}$ </tex-math></inline-formula> fault sensitivity performance is first proposed, which signifies the residual signal is robust to the external interference and sensitive to potential faults. Some parameters and slack matrices are introduced to obtain more relaxed conditions of designing the WFFDO with mixed performance. Afterward, a new online membership functions (MFs) iterative learning algorithm with the exponential decay learning rate is proposed for the sake of updating the observer MFs in real-time such that optimal <inline-formula> <tex-math>$L_{infty }/L_{2}$ </tex-math></inline-formula> performance can be achieved in this article. In addition, sufficient criterion is established so as to ensure the convergence of the structured mean squared error cost function by means of Lyapunov stability theory. Eventually, two simulation examples are given for illustrating the feasibility and superiority of the developed optimization FD technique.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1309-1321"},"PeriodicalIF":8.6,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993491","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 : 2024-12-03DOI: 10.1109/TSMC.2024.3502498
Meenakshi Gupta;Mingyuan Lei;Tat-Jen Cham;Hwee Kuan Lee
This article introduces a novel framework named double-latent optimization for representation disentanglement (D-LORD), which is designed for motion stylization (motion style transfer and motion retargeting). The primary objective of this framework is to separate the class and content information from a given motion sequence using a data-driven latent optimization approach. Here, class refers to person-specific style, such as a particular emotion or an individual’s identity, while content relates to the style-agnostic aspect of an action, such as walking or jumping, as universally understood concepts. The key advantage of D-LORD is its ability to perform style transfer without needing paired motion data. Instead, it utilizes class and content labels during the latent optimization process. By disentangling the representation, the framework enables the transformation of one motion sequence’s style to another’s style using adaptive instance normalization. The proposed D-LORD framework is designed with a focus on generalization, allowing it to handle different class and content labels for various applications. In addition, it can generate diverse motion sequences when specific class and content labels are provided. The framework’s efficacy is demonstrated through experimentation on three datasets: 1) the CMU XIA dataset for motion style transfer; 2) the multimodal human action database dataset; and 3) the RRIS Ability dataset for motion retargeting. Notably, this article presents the first generalized framework for motion style transfer and motion retargeting, showcasing its potential contributions in this area.
{"title":"D-LORD for Motion Stylization","authors":"Meenakshi Gupta;Mingyuan Lei;Tat-Jen Cham;Hwee Kuan Lee","doi":"10.1109/TSMC.2024.3502498","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3502498","url":null,"abstract":"This article introduces a novel framework named double-latent optimization for representation disentanglement (D-LORD), which is designed for motion stylization (motion style transfer and motion retargeting). The primary objective of this framework is to separate the class and content information from a given motion sequence using a data-driven latent optimization approach. Here, class refers to person-specific style, such as a particular emotion or an individual’s identity, while content relates to the style-agnostic aspect of an action, such as walking or jumping, as universally understood concepts. The key advantage of D-LORD is its ability to perform style transfer without needing paired motion data. Instead, it utilizes class and content labels during the latent optimization process. By disentangling the representation, the framework enables the transformation of one motion sequence’s style to another’s style using adaptive instance normalization. The proposed D-LORD framework is designed with a focus on generalization, allowing it to handle different class and content labels for various applications. In addition, it can generate diverse motion sequences when specific class and content labels are provided. The framework’s efficacy is demonstrated through experimentation on three datasets: 1) the CMU XIA dataset for motion style transfer; 2) the multimodal human action database dataset; and 3) the RRIS Ability dataset for motion retargeting. Notably, this article presents the first generalized framework for motion style transfer and motion retargeting, showcasing its potential contributions in this area.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1374-1387"},"PeriodicalIF":8.6,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993140","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 : 2024-11-28DOI: 10.1109/TSMC.2024.3493200
Keming Wu;Fuyuan Xiao;Yi Zhang
Complex evidence theory (CET), an extension of the traditional D-S evidence theory, has garnered academic interest for its capacity to articulate uncertainty through complex basic belief assignment (CBBA) and to perform uncertainty reasoning using complex combination rules. Nonetheless, quantifying uncertainty within CET remains a subject of ongoing research. To enhance decision making, a method for complex pignistic belief transformation (CPBT) has been introduced, which allocates CBBAs of multielement focal elements to subsets. CPBT’s core lies in the fractal-inspired redistribution of the complex mass function. This article presents an experimental simulation and analysis of CPBT’s generation process along the temporal dimension, rooted in fractal theory. Subsequently, a novel fractal-based complex belief (FCB) entropy is proposed to gauge the uncertainty of CBBA. The properties of FCB entropy are examined, and its efficacy is demonstrated through various numerical examples and practical application.
{"title":"A Fractal-Based Complex Belief Entropy for Uncertainty Measure in Complex Evidence Theory","authors":"Keming Wu;Fuyuan Xiao;Yi Zhang","doi":"10.1109/TSMC.2024.3493200","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3493200","url":null,"abstract":"Complex evidence theory (CET), an extension of the traditional D-S evidence theory, has garnered academic interest for its capacity to articulate uncertainty through complex basic belief assignment (CBBA) and to perform uncertainty reasoning using complex combination rules. Nonetheless, quantifying uncertainty within CET remains a subject of ongoing research. To enhance decision making, a method for complex pignistic belief transformation (CPBT) has been introduced, which allocates CBBAs of multielement focal elements to subsets. CPBT’s core lies in the fractal-inspired redistribution of the complex mass function. This article presents an experimental simulation and analysis of CPBT’s generation process along the temporal dimension, rooted in fractal theory. Subsequently, a novel fractal-based complex belief (FCB) entropy is proposed to gauge the uncertainty of CBBA. The properties of FCB entropy are examined, and its efficacy is demonstrated through various numerical examples and practical application.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"910-924"},"PeriodicalIF":8.6,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993450","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 : 2024-11-28DOI: 10.1109/TSMC.2024.3497961
Huaguang Zhang;Xiaohui Yue;Jiayue Sun;Xiyue Guo
This article studies a prescribed finite-time consensus problem for uncertain nonlinear multiagent systems (MASs) with event-triggered updates. First, the novel finite-time performance boundaries are proposed to ensure that consensus deviations converge to the predefined steady-state zones within a preassigned time, and by using asymmetrically parallel boundaries to constrain consensus errors to narrow feasible regions, small overshoots of consensus errors are assured. Second, by utilizing the inherent approximation property of fuzzy logic systems (FLSs), a fuzzy state observer is devised to recover the unmeasurable states. Based on the observation outcomes, an improved event-triggered output-feedback controller is synthesized so that the number of control input updates is reduced without incurring an evidently deteriorated control performance. The salient merits of the proposed approach are that all consensus errors are free from great overshoots, while settling time can be explicitly assigned in advance. Finally, two examples are given to verify the validity of theoretical results.
{"title":"Prescribed Finite-Time Fuzzy Consensus Control for Multiagent Systems With Aperiodic Updates","authors":"Huaguang Zhang;Xiaohui Yue;Jiayue Sun;Xiyue Guo","doi":"10.1109/TSMC.2024.3497961","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3497961","url":null,"abstract":"This article studies a prescribed finite-time consensus problem for uncertain nonlinear multiagent systems (MASs) with event-triggered updates. First, the novel finite-time performance boundaries are proposed to ensure that consensus deviations converge to the predefined steady-state zones within a preassigned time, and by using asymmetrically parallel boundaries to constrain consensus errors to narrow feasible regions, small overshoots of consensus errors are assured. Second, by utilizing the inherent approximation property of fuzzy logic systems (FLSs), a fuzzy state observer is devised to recover the unmeasurable states. Based on the observation outcomes, an improved event-triggered output-feedback controller is synthesized so that the number of control input updates is reduced without incurring an evidently deteriorated control performance. The salient merits of the proposed approach are that all consensus errors are free from great overshoots, while settling time can be explicitly assigned in advance. Finally, two examples are given to verify the validity of theoretical results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1362-1373"},"PeriodicalIF":8.6,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993137","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 an adaptive fault-tolerant control (FTC) scheme for heterogeneous multiagent systems with time-varying communication link faults and actuator faults. First, the communication link faults, including the channel signal fading and cyber bias attack, is considered, and the communication link fault compensation controller is designed through introducing the adaptive signals with the estimate of the norms of the faulty matrix. Then, by using the minimum eigenvalue of the control gain matrix, the minimum-eigenvalue-based adaptive fault-tolerant controller is proposed to compensate for the time-varying actuator loss of effectiveness and bias faults. Moreover, the convergence performance analysis of the developed FTC algorithm is given based on the Lyapunov theory. The simulation results carried out on the quadrotors-unmanned ground vehicles formation systems validate the effectiveness of the theoretical results.
{"title":"An Adaptive Fault-Tolerant Control Scheme for Heterogeneous Multiagent Systems","authors":"Jianye Gong;Yajie Ma;Bin Jiang;Youmin Zhang;Li Guo","doi":"10.1109/TSMC.2024.3496717","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3496717","url":null,"abstract":"This article proposes an adaptive fault-tolerant control (FTC) scheme for heterogeneous multiagent systems with time-varying communication link faults and actuator faults. First, the communication link faults, including the channel signal fading and cyber bias attack, is considered, and the communication link fault compensation controller is designed through introducing the adaptive signals with the estimate of the norms of the faulty matrix. Then, by using the minimum eigenvalue of the control gain matrix, the minimum-eigenvalue-based adaptive fault-tolerant controller is proposed to compensate for the time-varying actuator loss of effectiveness and bias faults. Moreover, the convergence performance analysis of the developed FTC algorithm is given based on the Lyapunov theory. The simulation results carried out on the quadrotors-unmanned ground vehicles formation systems validate the effectiveness of the theoretical results.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1264-1276"},"PeriodicalIF":8.6,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993392","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 : 2024-11-28DOI: 10.1109/TSMC.2024.3502446
Kürşad Metehan Gül;Tufan Kumbasar
This study revisits the fuzzy control system design problem with the motto “Fuzzy with Conventional Control,” inspired by L.A. Zadeh’s statement in the famous debate “Some Crisp Thoughts on the Fuzzy versus Conventional Control.” Focused on single-input (SI) fuzzy PIDs (FPIDs), our approach synergizes fuzzy and conventional control, presenting similar control laws to PID and fuzzy gain-scheduled (FGS) PID. Departing from traditional fuzzy control paradigms, our design methodology enhances, rather than replaces, PID controllers with fuzzy logic controllers (FLCs). We start by analyzing the internal structure of both type-1 and type-2 SI-FPIDs and commenting on their structural properties. We address the high-design complexity of FLCs by proposing an interpretable and geometrical design method that explicitly shapes fuzzy mapping (FM) according to the desired control characteristics. To provide self-tuning (ST) capability to the FPID, like the FGS-PID, we develop ST mechanisms that adapt the FM of SI-FPID according to the operating point via the derived insights. Real-world application in speed control for an industrial permanent magnet synchronous machine validates the efficacy of our designs, showcasing improved disturbance rejection and reduced control signal variation compared to FGS-PIDs and PID. This research advocates for the wider adoption of SI-FPID as a practical enhancement to PID in industrial applications, offering design simplicity and ST capabilities.
{"title":"Back to the Future: Synergizing Fuzzy and Conventional Control","authors":"Kürşad Metehan Gül;Tufan Kumbasar","doi":"10.1109/TSMC.2024.3502446","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3502446","url":null,"abstract":"This study revisits the fuzzy control system design problem with the motto “Fuzzy with Conventional Control,” inspired by L.A. Zadeh’s statement in the famous debate “Some Crisp Thoughts on the Fuzzy versus Conventional Control.” Focused on single-input (SI) fuzzy PIDs (FPIDs), our approach synergizes fuzzy and conventional control, presenting similar control laws to PID and fuzzy gain-scheduled (FGS) PID. Departing from traditional fuzzy control paradigms, our design methodology enhances, rather than replaces, PID controllers with fuzzy logic controllers (FLCs). We start by analyzing the internal structure of both type-1 and type-2 SI-FPIDs and commenting on their structural properties. We address the high-design complexity of FLCs by proposing an interpretable and geometrical design method that explicitly shapes fuzzy mapping (FM) according to the desired control characteristics. To provide self-tuning (ST) capability to the FPID, like the FGS-PID, we develop ST mechanisms that adapt the FM of SI-FPID according to the operating point via the derived insights. Real-world application in speed control for an industrial permanent magnet synchronous machine validates the efficacy of our designs, showcasing improved disturbance rejection and reduced control signal variation compared to FGS-PIDs and PID. This research advocates for the wider adoption of SI-FPID as a practical enhancement to PID in industrial applications, offering design simplicity and ST capabilities.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1413-1424"},"PeriodicalIF":8.6,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993482","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 : 2024-11-27DOI: 10.1109/TSMC.2024.3495707
Xiuyu Zhang;Pukun Lu;Chenliang Wang;Guoqiang Zhu;Xin Zhang;Xinkai Chen;Chun-Yi Su
Taking into consideration the issue of the quadrotor unmanned aircraft robots (UARs) actuated by motors with hysteresis input, this research presents an adaptive dynamic implicit inverse control technique based on neural networks to achieve the desired trajectories. The following summarizes the primary technologies: 1) the hysteresis effect in UARs has been considered and eliminated by the proposed implicit inverse algorithms, which means a searching method for acquiring the real control signals is designed resulting in selecting to avoid constructing the hysteresis direct inverse model; 2) precise tracking is accomplished by designing an adaptive dynamic surface control (DSC) technology with enhanced state observer under the constraint that only the position data is available. In the meanwhile, the $L_{infty }$ performance can be obtained by selecting the suitable parameters; and 3) the underactuated Drone platform has been constructed as well as the control results have implemented to confirm that the successful application of the proposed implicit inverse control algorithms.
{"title":"Adaptive Observer-Based Implicit Inverse Control for Quadrotor Unmanned Aircraft Robots and Experimental Validation on the QDrone Platform","authors":"Xiuyu Zhang;Pukun Lu;Chenliang Wang;Guoqiang Zhu;Xin Zhang;Xinkai Chen;Chun-Yi Su","doi":"10.1109/TSMC.2024.3495707","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3495707","url":null,"abstract":"Taking into consideration the issue of the quadrotor unmanned aircraft robots (UARs) actuated by motors with hysteresis input, this research presents an adaptive dynamic implicit inverse control technique based on neural networks to achieve the desired trajectories. The following summarizes the primary technologies: 1) the hysteresis effect in UARs has been considered and eliminated by the proposed implicit inverse algorithms, which means a searching method for acquiring the real control signals is designed resulting in selecting to avoid constructing the hysteresis direct inverse model; 2) precise tracking is accomplished by designing an adaptive dynamic surface control (DSC) technology with enhanced state observer under the constraint that only the position data is available. In the meanwhile, the <inline-formula> <tex-math>$L_{infty }$ </tex-math></inline-formula> performance can be obtained by selecting the suitable parameters; and 3) the underactuated Drone platform has been constructed as well as the control results have implemented to confirm that the successful application of the proposed implicit inverse control algorithms.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"1163-1174"},"PeriodicalIF":8.6,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993452","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 : 2024-11-27DOI: 10.1109/TSMC.2024.3489029
Surochita Pal;Sushmita Mitra;B. Uma Shankar
The computerized delineation and prognosis of lung cancer is typically based on Computed Tomography (CT) image analysis, whereby the region of interest (ROI) is accurately demarcated and classified. Deep learning in computer vision provides a different perspective to image segmentation. Due to the increasing number of cases of lung cancer and the availability of large volumes of CT scans every day, the need for automated handling becomes imperative. This requires efficient delineation and diagnosis through the design of new techniques for improved accuracy. In this article, we introduce the novel Weighted Deformable U-Net (WDU-Net) for efficient delineation of the tumor region. It incorporates the Deformable Convolution (DC) that can model arbitrary geometric shapes of region of interests. This is enhanced by the Weight Generation (WG) module to suppress unimportant features while highlighting relevant ones. A new Focal Asymmetric Similarity (FAS) loss function helps handle class imbalance. Ablation studies and comparison with state-of-the-art models help establish the effectiveness of WDU-Net with ensemble learning, tested on five publicly available lung cancer datasets. Best results were obtained on the LIDC-IDRI lung tumor test dataset, with an average Dice score of 0.9137, the Hausdorff Distance 95% (HD95) of 5.3852, and Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.9449.
{"title":"Weighted Deformable Network for Efficient Segmentation of Lung Tumors in CT","authors":"Surochita Pal;Sushmita Mitra;B. Uma Shankar","doi":"10.1109/TSMC.2024.3489029","DOIUrl":"https://doi.org/10.1109/TSMC.2024.3489029","url":null,"abstract":"The computerized delineation and prognosis of lung cancer is typically based on Computed Tomography (CT) image analysis, whereby the region of interest (ROI) is accurately demarcated and classified. Deep learning in computer vision provides a different perspective to image segmentation. Due to the increasing number of cases of lung cancer and the availability of large volumes of CT scans every day, the need for automated handling becomes imperative. This requires efficient delineation and diagnosis through the design of new techniques for improved accuracy. In this article, we introduce the novel Weighted Deformable U-Net (WDU-Net) for efficient delineation of the tumor region. It incorporates the Deformable Convolution (DC) that can model arbitrary geometric shapes of region of interests. This is enhanced by the Weight Generation (WG) module to suppress unimportant features while highlighting relevant ones. A new Focal Asymmetric Similarity (FAS) loss function helps handle class imbalance. Ablation studies and comparison with state-of-the-art models help establish the effectiveness of WDU-Net with ensemble learning, tested on five publicly available lung cancer datasets. Best results were obtained on the LIDC-IDRI lung tumor test dataset, with an average Dice score of 0.9137, the Hausdorff Distance 95% (HD95) of 5.3852, and Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.9449.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 2","pages":"898-909"},"PeriodicalIF":8.6,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993449","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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