According to the robot’s walking motion characteristics, the position/force switching control is studied to realize the segmental control of the robot stroke. This stroke is controlled by position when the foot end of the robot descends from the suspension to the ground. To avoid excessive contact force when the robot touches the ground, force control is carried out when the foot touches the ground. Due to the force and position control methods and control parameters of the hydraulic quadruped robots are different, the precise mathematical model for the joint position control and joint force control of the leg joints of the hydraulic quadruped robot is established using the system identification method. A fuzzy multi-model switching algorithm is proposed to solve the problem of jumping and jitter of system parameters in the process of force/position switching. Through simulation and prototype experiments, fuzzy multi-model switching is compared with direct switching and multi-model switching, and the switching effect of the algorithm is verified.
{"title":"Research on force/position switching control of servo actuator for hydraulically driven joint robot","authors":"Bing-Tuan Gao, Yongkang Wang, Wenlong Han, Shilong Xue","doi":"10.1177/01423312241227096","DOIUrl":"https://doi.org/10.1177/01423312241227096","url":null,"abstract":"According to the robot’s walking motion characteristics, the position/force switching control is studied to realize the segmental control of the robot stroke. This stroke is controlled by position when the foot end of the robot descends from the suspension to the ground. To avoid excessive contact force when the robot touches the ground, force control is carried out when the foot touches the ground. Due to the force and position control methods and control parameters of the hydraulic quadruped robots are different, the precise mathematical model for the joint position control and joint force control of the leg joints of the hydraulic quadruped robot is established using the system identification method. A fuzzy multi-model switching algorithm is proposed to solve the problem of jumping and jitter of system parameters in the process of force/position switching. Through simulation and prototype experiments, fuzzy multi-model switching is compared with direct switching and multi-model switching, and the switching effect of the algorithm is verified.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"20 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139783402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1177/01423312241228782
H. Min, Zhicheng Wei
In this paper, we investigate the state-feedback control for nonlinear systems with a prescribed upper bound of the settling time. First, a prescribed-time stability theorem using Lyapunov analysis and a uniformly bounded scaling function is proposed. Then, based on this theorem and the backstepping technique, a finite-time control procedure is provided for the uncertain nonlinear systems with unmatched nonlinear terms. Based on the design procedure, a state-feedback controller is obtained, which can render the system states exactly convergent to zero in a prescribed time and maintain at zero thereafter. Finally, simulation examples are used to demonstrate the effectiveness of the proposed scheme.
{"title":"Prescribed-time state-feedback stabilization of nonlinear systems with unmatched nonlinear terms","authors":"H. Min, Zhicheng Wei","doi":"10.1177/01423312241228782","DOIUrl":"https://doi.org/10.1177/01423312241228782","url":null,"abstract":"In this paper, we investigate the state-feedback control for nonlinear systems with a prescribed upper bound of the settling time. First, a prescribed-time stability theorem using Lyapunov analysis and a uniformly bounded scaling function is proposed. Then, based on this theorem and the backstepping technique, a finite-time control procedure is provided for the uncertain nonlinear systems with unmatched nonlinear terms. Based on the design procedure, a state-feedback controller is obtained, which can render the system states exactly convergent to zero in a prescribed time and maintain at zero thereafter. Finally, simulation examples are used to demonstrate the effectiveness of the proposed scheme.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"33 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139784838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1177/01423312231217767
Annadurai Sadhasivam, Nageswari Sathyamoorthy
In the current landscape of renewable energy systems, optimizing the performance of power electronic converters is crucial for ensuring reliability. Within the realm of direct current (DC)–DC power converter systems, the differential power processing (DPP) converter holds promise. However, realizing its full potential requires meticulous system design, especially in response to varying solar irradiation levels. Poor design can result in performance degradation, leading to system damage and voltage instability due to sudden irradiation fluctuations. To address these challenges, this study investigates the performance optimization of a DPP converter enhanced with a modified switched inductor, tailored for solar photovoltaic applications. To overcome traditional control strategy limitations, we propose an innovative enhanced fuzzy logic controller (E-FLC). This controller’s strength lies in its dynamic adaptability, achieved through variable duty cycle control, input parameters, membership functions, and output responses. This paper emphasizes methodological precision, particularly in applying the E-FLC to the modified switched inductor. The use of this controller significantly improves both steady-state and transient response performance compared to traditional switched inductors. It rigorously analyzes the responses of the DPP converter under steady-state and transient conditions, with and without the modified switched inductor. This analytical approach sheds light on a critical yet often overlooked aspect of photovoltaic systems. The core innovation driving this research is the adoption of the E-FLC, which outperforms the commonly used proportional–integral (PI) controller in steady-state performance and transient response characteristics. This paper goes beyond conventional converter optimization studies by introducing a holistic approach encompassing system dynamics, control strategy innovation, and performance evaluation. The proposed E-FLC represents a methodological breakthrough and a substantial improvement in converter efficiency and reliability. As renewable energy continues to reshape the global energy landscape, this research sets a new standard for harnessing the true capabilities of power electronic converters in solar photovoltaic systems.
{"title":"Performance analysis of optimized differential power processing converter with switched inductor using enhanced fuzzy logic control for solar photovoltaic systems","authors":"Annadurai Sadhasivam, Nageswari Sathyamoorthy","doi":"10.1177/01423312231217767","DOIUrl":"https://doi.org/10.1177/01423312231217767","url":null,"abstract":"In the current landscape of renewable energy systems, optimizing the performance of power electronic converters is crucial for ensuring reliability. Within the realm of direct current (DC)–DC power converter systems, the differential power processing (DPP) converter holds promise. However, realizing its full potential requires meticulous system design, especially in response to varying solar irradiation levels. Poor design can result in performance degradation, leading to system damage and voltage instability due to sudden irradiation fluctuations. To address these challenges, this study investigates the performance optimization of a DPP converter enhanced with a modified switched inductor, tailored for solar photovoltaic applications. To overcome traditional control strategy limitations, we propose an innovative enhanced fuzzy logic controller (E-FLC). This controller’s strength lies in its dynamic adaptability, achieved through variable duty cycle control, input parameters, membership functions, and output responses. This paper emphasizes methodological precision, particularly in applying the E-FLC to the modified switched inductor. The use of this controller significantly improves both steady-state and transient response performance compared to traditional switched inductors. It rigorously analyzes the responses of the DPP converter under steady-state and transient conditions, with and without the modified switched inductor. This analytical approach sheds light on a critical yet often overlooked aspect of photovoltaic systems. The core innovation driving this research is the adoption of the E-FLC, which outperforms the commonly used proportional–integral (PI) controller in steady-state performance and transient response characteristics. This paper goes beyond conventional converter optimization studies by introducing a holistic approach encompassing system dynamics, control strategy innovation, and performance evaluation. The proposed E-FLC represents a methodological breakthrough and a substantial improvement in converter efficiency and reliability. As renewable energy continues to reshape the global energy landscape, this research sets a new standard for harnessing the true capabilities of power electronic converters in solar photovoltaic systems.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"82 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1177/01423312231217767
Annadurai Sadhasivam, Nageswari Sathyamoorthy
In the current landscape of renewable energy systems, optimizing the performance of power electronic converters is crucial for ensuring reliability. Within the realm of direct current (DC)–DC power converter systems, the differential power processing (DPP) converter holds promise. However, realizing its full potential requires meticulous system design, especially in response to varying solar irradiation levels. Poor design can result in performance degradation, leading to system damage and voltage instability due to sudden irradiation fluctuations. To address these challenges, this study investigates the performance optimization of a DPP converter enhanced with a modified switched inductor, tailored for solar photovoltaic applications. To overcome traditional control strategy limitations, we propose an innovative enhanced fuzzy logic controller (E-FLC). This controller’s strength lies in its dynamic adaptability, achieved through variable duty cycle control, input parameters, membership functions, and output responses. This paper emphasizes methodological precision, particularly in applying the E-FLC to the modified switched inductor. The use of this controller significantly improves both steady-state and transient response performance compared to traditional switched inductors. It rigorously analyzes the responses of the DPP converter under steady-state and transient conditions, with and without the modified switched inductor. This analytical approach sheds light on a critical yet often overlooked aspect of photovoltaic systems. The core innovation driving this research is the adoption of the E-FLC, which outperforms the commonly used proportional–integral (PI) controller in steady-state performance and transient response characteristics. This paper goes beyond conventional converter optimization studies by introducing a holistic approach encompassing system dynamics, control strategy innovation, and performance evaluation. The proposed E-FLC represents a methodological breakthrough and a substantial improvement in converter efficiency and reliability. As renewable energy continues to reshape the global energy landscape, this research sets a new standard for harnessing the true capabilities of power electronic converters in solar photovoltaic systems.
{"title":"Performance analysis of optimized differential power processing converter with switched inductor using enhanced fuzzy logic control for solar photovoltaic systems","authors":"Annadurai Sadhasivam, Nageswari Sathyamoorthy","doi":"10.1177/01423312231217767","DOIUrl":"https://doi.org/10.1177/01423312231217767","url":null,"abstract":"In the current landscape of renewable energy systems, optimizing the performance of power electronic converters is crucial for ensuring reliability. Within the realm of direct current (DC)–DC power converter systems, the differential power processing (DPP) converter holds promise. However, realizing its full potential requires meticulous system design, especially in response to varying solar irradiation levels. Poor design can result in performance degradation, leading to system damage and voltage instability due to sudden irradiation fluctuations. To address these challenges, this study investigates the performance optimization of a DPP converter enhanced with a modified switched inductor, tailored for solar photovoltaic applications. To overcome traditional control strategy limitations, we propose an innovative enhanced fuzzy logic controller (E-FLC). This controller’s strength lies in its dynamic adaptability, achieved through variable duty cycle control, input parameters, membership functions, and output responses. This paper emphasizes methodological precision, particularly in applying the E-FLC to the modified switched inductor. The use of this controller significantly improves both steady-state and transient response performance compared to traditional switched inductors. It rigorously analyzes the responses of the DPP converter under steady-state and transient conditions, with and without the modified switched inductor. This analytical approach sheds light on a critical yet often overlooked aspect of photovoltaic systems. The core innovation driving this research is the adoption of the E-FLC, which outperforms the commonly used proportional–integral (PI) controller in steady-state performance and transient response characteristics. This paper goes beyond conventional converter optimization studies by introducing a holistic approach encompassing system dynamics, control strategy innovation, and performance evaluation. The proposed E-FLC represents a methodological breakthrough and a substantial improvement in converter efficiency and reliability. As renewable energy continues to reshape the global energy landscape, this research sets a new standard for harnessing the true capabilities of power electronic converters in solar photovoltaic systems.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.1177/01423312241227539
Donglei Dong, Xianbo Xiang, Jinjiang Li, Shaolong Yang
Due to the nonlinearity, strong coupling, and uncertain parameters of autonomous underwater vehicle (AUV), it is difficult to build an accurate dynamic model, which makes precise control of AUV extremely challenging. To handle the precise heading-following problem of AUV, this paper proposes an iterative learning-based redefine model-free adaptive heading control (IL-RMFAC) method for the underactuated AUV with unknown disturbances based on data driven. The control scheme consists of a learning control algorithm, a parameter iterative update algorithm, and a parameter reset algorithm. It is designed using only the input and output (I/O) data of the controlled system and is a data-driven control method. The pseudo partial derivative (PPD) can be iteratively calculated through the parameter iterative update algorithm and reset algorithm to adjust the learning gain, solving the problem of strictly limited initial position of the traditional fixed learning gain iterative learning control (ILC). A linear combination of angle and angular velocity is introduced in the kinematic layer to avoid overshooting of the expected following target, and an iterative learning method is introduced in the dynamics to improve the accuracy. As the number of iterations increases, the steady-state error is gradually decreased. Finally, by comparing traditional proportional–integral–derivative (PID) simulations, the proposed algorithm’s effectiveness and outstanding performance for the AUV heading tracking are confirmed.
{"title":"Iterative learning–based model-free adaptive precise heading following of an autonomous underwater vehicle with unknown disturbances","authors":"Donglei Dong, Xianbo Xiang, Jinjiang Li, Shaolong Yang","doi":"10.1177/01423312241227539","DOIUrl":"https://doi.org/10.1177/01423312241227539","url":null,"abstract":"Due to the nonlinearity, strong coupling, and uncertain parameters of autonomous underwater vehicle (AUV), it is difficult to build an accurate dynamic model, which makes precise control of AUV extremely challenging. To handle the precise heading-following problem of AUV, this paper proposes an iterative learning-based redefine model-free adaptive heading control (IL-RMFAC) method for the underactuated AUV with unknown disturbances based on data driven. The control scheme consists of a learning control algorithm, a parameter iterative update algorithm, and a parameter reset algorithm. It is designed using only the input and output (I/O) data of the controlled system and is a data-driven control method. The pseudo partial derivative (PPD) can be iteratively calculated through the parameter iterative update algorithm and reset algorithm to adjust the learning gain, solving the problem of strictly limited initial position of the traditional fixed learning gain iterative learning control (ILC). A linear combination of angle and angular velocity is introduced in the kinematic layer to avoid overshooting of the expected following target, and an iterative learning method is introduced in the dynamics to improve the accuracy. As the number of iterations increases, the steady-state error is gradually decreased. Finally, by comparing traditional proportional–integral–derivative (PID) simulations, the proposed algorithm’s effectiveness and outstanding performance for the AUV heading tracking are confirmed.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"179 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139843177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1177/01423312231207682
Anan Gao, Aihua Hu, Yinghua Jin, Zhengxian Jiang
This paper investigates the mean-square bounded consensus issue in a two-layer multi-agent network under deception attacks. The two-layer network is composed of the leader and follower layers with a switching topology. Employing an impulsive control method, the mean-square bounded consensus for the leader layer and the node-to-node mean-square bounded consensus of the two-layer network are analyzed. Based on the knowledge of graph theory, Lyapunov stability theory, and linear matrix inequalities, sufficient conditions for the mean-square bounded consensus of multi-agent systems in the two-layer network are derived. Finally, the practicability and efficacy of the theoretical outcomes are corroborated via the provided numerical simulations.
{"title":"Impulsive bounded consensus of two-layer multi-agent networks under deception attacks","authors":"Anan Gao, Aihua Hu, Yinghua Jin, Zhengxian Jiang","doi":"10.1177/01423312231207682","DOIUrl":"https://doi.org/10.1177/01423312231207682","url":null,"abstract":"This paper investigates the mean-square bounded consensus issue in a two-layer multi-agent network under deception attacks. The two-layer network is composed of the leader and follower layers with a switching topology. Employing an impulsive control method, the mean-square bounded consensus for the leader layer and the node-to-node mean-square bounded consensus of the two-layer network are analyzed. Based on the knowledge of graph theory, Lyapunov stability theory, and linear matrix inequalities, sufficient conditions for the mean-square bounded consensus of multi-agent systems in the two-layer network are derived. Finally, the practicability and efficacy of the theoretical outcomes are corroborated via the provided numerical simulations.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"66 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139861246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1177/01423312231217761
Manish Yadav, Hirenkumar G. Patel, S. Nagarsheth
In process industries, cascade control is comprehensively used for disturbance attenuation. This manuscript presents the control of the non-minimum phase (NMP) system with dead time via a series cascade scheme. An improved fractional-filter-based control scheme encompassing inverse and dead time compensators with analytical tuning is proposed. The design hinges on an enhanced Bode’s ideal transfer function, which incorporates delay and NMP zero to deal with the system’s NMP and dead time. Particle swarm optimization (PSO) is utilized to obtain the optimal assessment of fractional filter-based controller settings by minimizing an objective function. Two benchmark problems are presented to test the efficacy of the recommended controller. The Riemann surface and sensitivity examination are used to realize the stability and robustness of the feedback design. Numerical simulations exhibit the superiority of the suggested controller for closed-loop results.
{"title":"Optimal fractional-order series cascade controller design: A refined Bode’s ideal transfer function perspective","authors":"Manish Yadav, Hirenkumar G. Patel, S. Nagarsheth","doi":"10.1177/01423312231217761","DOIUrl":"https://doi.org/10.1177/01423312231217761","url":null,"abstract":"In process industries, cascade control is comprehensively used for disturbance attenuation. This manuscript presents the control of the non-minimum phase (NMP) system with dead time via a series cascade scheme. An improved fractional-filter-based control scheme encompassing inverse and dead time compensators with analytical tuning is proposed. The design hinges on an enhanced Bode’s ideal transfer function, which incorporates delay and NMP zero to deal with the system’s NMP and dead time. Particle swarm optimization (PSO) is utilized to obtain the optimal assessment of fractional filter-based controller settings by minimizing an objective function. Two benchmark problems are presented to test the efficacy of the recommended controller. The Riemann surface and sensitivity examination are used to realize the stability and robustness of the feedback design. Numerical simulations exhibit the superiority of the suggested controller for closed-loop results.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"48 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139862143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1177/01423312231225992
Chiheb Ben Regaya, Fethi Farhani, Hichem Hamdi, A. Zaafouri, Abdelkader Chaari
Maximum power point tracking (MPPT) controller is the main element in photovoltaic (PV) systems, which is used to ensure maximum power extraction under different meteorological conditions. A MPPT controller can guarantee good performance criteria even in the presence of climatic changes. To achieve this goal, several techniques have been proposed in the literature to improve robustness of the PV system control, such as artificial intelligence and multiswarm particle swarm optimization (MSPSO) algorithm. Previous research on classical MSPSO has shown that the algorithm search behavior cannot find the optimal solution for certain problems. In this context, we investigate the design of a new MPPT controller based on a modified version of heterogeneous multiswarm particle swarm optimization algorithm using an adaptive factor selection strategy (FMSPSO) for PV systems. The proposed FMSPSO can improve the tracking capability with high accuracy, less oscillations, and high robustness. To validate the proposed solution, a simulation and experimental benchmarking of a PV system are presented and analyzed. The obtained results show the effectiveness of the proposed solution compared with the classical MSPSO, fuzzy logic, and perturb and observe (P&O) control presented in other recent works.
{"title":"A new MPPT controller based on a modified multiswarm PSO algorithm using an adaptive factor selection strategy for partially shaded PV systems","authors":"Chiheb Ben Regaya, Fethi Farhani, Hichem Hamdi, A. Zaafouri, Abdelkader Chaari","doi":"10.1177/01423312231225992","DOIUrl":"https://doi.org/10.1177/01423312231225992","url":null,"abstract":"Maximum power point tracking (MPPT) controller is the main element in photovoltaic (PV) systems, which is used to ensure maximum power extraction under different meteorological conditions. A MPPT controller can guarantee good performance criteria even in the presence of climatic changes. To achieve this goal, several techniques have been proposed in the literature to improve robustness of the PV system control, such as artificial intelligence and multiswarm particle swarm optimization (MSPSO) algorithm. Previous research on classical MSPSO has shown that the algorithm search behavior cannot find the optimal solution for certain problems. In this context, we investigate the design of a new MPPT controller based on a modified version of heterogeneous multiswarm particle swarm optimization algorithm using an adaptive factor selection strategy (FMSPSO) for PV systems. The proposed FMSPSO can improve the tracking capability with high accuracy, less oscillations, and high robustness. To validate the proposed solution, a simulation and experimental benchmarking of a PV system are presented and analyzed. The obtained results show the effectiveness of the proposed solution compared with the classical MSPSO, fuzzy logic, and perturb and observe (P&O) control presented in other recent works.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"150 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139858686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1177/01423312231207682
Anan Gao, Aihua Hu, Yinghua Jin, Zhengxian Jiang
This paper investigates the mean-square bounded consensus issue in a two-layer multi-agent network under deception attacks. The two-layer network is composed of the leader and follower layers with a switching topology. Employing an impulsive control method, the mean-square bounded consensus for the leader layer and the node-to-node mean-square bounded consensus of the two-layer network are analyzed. Based on the knowledge of graph theory, Lyapunov stability theory, and linear matrix inequalities, sufficient conditions for the mean-square bounded consensus of multi-agent systems in the two-layer network are derived. Finally, the practicability and efficacy of the theoretical outcomes are corroborated via the provided numerical simulations.
{"title":"Impulsive bounded consensus of two-layer multi-agent networks under deception attacks","authors":"Anan Gao, Aihua Hu, Yinghua Jin, Zhengxian Jiang","doi":"10.1177/01423312231207682","DOIUrl":"https://doi.org/10.1177/01423312231207682","url":null,"abstract":"This paper investigates the mean-square bounded consensus issue in a two-layer multi-agent network under deception attacks. The two-layer network is composed of the leader and follower layers with a switching topology. Employing an impulsive control method, the mean-square bounded consensus for the leader layer and the node-to-node mean-square bounded consensus of the two-layer network are analyzed. Based on the knowledge of graph theory, Lyapunov stability theory, and linear matrix inequalities, sufficient conditions for the mean-square bounded consensus of multi-agent systems in the two-layer network are derived. Finally, the practicability and efficacy of the theoretical outcomes are corroborated via the provided numerical simulations.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"92 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139801228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.1177/01423312231217761
Manish Yadav, Hirenkumar G. Patel, S. Nagarsheth
In process industries, cascade control is comprehensively used for disturbance attenuation. This manuscript presents the control of the non-minimum phase (NMP) system with dead time via a series cascade scheme. An improved fractional-filter-based control scheme encompassing inverse and dead time compensators with analytical tuning is proposed. The design hinges on an enhanced Bode’s ideal transfer function, which incorporates delay and NMP zero to deal with the system’s NMP and dead time. Particle swarm optimization (PSO) is utilized to obtain the optimal assessment of fractional filter-based controller settings by minimizing an objective function. Two benchmark problems are presented to test the efficacy of the recommended controller. The Riemann surface and sensitivity examination are used to realize the stability and robustness of the feedback design. Numerical simulations exhibit the superiority of the suggested controller for closed-loop results.
{"title":"Optimal fractional-order series cascade controller design: A refined Bode’s ideal transfer function perspective","authors":"Manish Yadav, Hirenkumar G. Patel, S. Nagarsheth","doi":"10.1177/01423312231217761","DOIUrl":"https://doi.org/10.1177/01423312231217761","url":null,"abstract":"In process industries, cascade control is comprehensively used for disturbance attenuation. This manuscript presents the control of the non-minimum phase (NMP) system with dead time via a series cascade scheme. An improved fractional-filter-based control scheme encompassing inverse and dead time compensators with analytical tuning is proposed. The design hinges on an enhanced Bode’s ideal transfer function, which incorporates delay and NMP zero to deal with the system’s NMP and dead time. Particle swarm optimization (PSO) is utilized to obtain the optimal assessment of fractional filter-based controller settings by minimizing an objective function. Two benchmark problems are presented to test the efficacy of the recommended controller. The Riemann surface and sensitivity examination are used to realize the stability and robustness of the feedback design. Numerical simulations exhibit the superiority of the suggested controller for closed-loop results.","PeriodicalId":507087,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"74 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139802283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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