In this paper, we introduce a new concept termed global temporal observability for continuous and discrete linear dynamic systems and explore its connection with the classical notion of observability. It is shown that, as a concept, global temporal observability is a generalization of the classical observability. However, as a feature of a dynamic system, global temporal observability is embedded into classical observability. The necessary condition for global temporal observability is presented. Four linear systems were considered to test the proposed concept. Since observability is a binary test, our results matched the results of classical observability analysis when appropriate basis functions are utilized. The advantages and disadvantages of the proposed concept are discussed. The main advantage of global temporal observability is that it restores the state function for the entire time duration in a single step that requires matrix inversion. It is shown that global temporal observability connects state reconstruction, differential equations, and observability concepts.
{"title":"Global temporal observability of linear dynamic systems","authors":"Altay Zhakatayev , Yuriy Rogovchenko , Matthias Pätzold","doi":"10.1016/j.ifacsc.2025.100312","DOIUrl":"10.1016/j.ifacsc.2025.100312","url":null,"abstract":"<div><div>In this paper, we introduce a new concept termed global temporal observability for continuous and discrete linear dynamic systems and explore its connection with the classical notion of observability. It is shown that, as a concept, global temporal observability is a generalization of the classical observability. However, as a feature of a dynamic system, global temporal observability is embedded into classical observability. The necessary condition for global temporal observability is presented. Four linear systems were considered to test the proposed concept. Since observability is a binary test, our results matched the results of classical observability analysis when appropriate basis functions are utilized. The advantages and disadvantages of the proposed concept are discussed. The main advantage of global temporal observability is that it restores the state function for the entire time duration in a single step that requires matrix inversion. It is shown that global temporal observability connects state reconstruction, differential equations, and observability concepts.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100312"},"PeriodicalIF":1.8,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928557","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}
As far as climate change is concerned, a recurrent question that is asked either at the government or a consumer level is: Why should I make efforts to reduce my CO emission levels whereas the others will not make these efforts? The present paper provides qualitative elements to this question when asked at the government level. More precisely, we assume that each country wants to maximize a tradeoff between an individual benefit brought by emitting CO and an economical damage due to climate change while being influenced by the reduction strategies of the other countries. The influence term is key for the analysis and enables more virtuous or cooperative behavior. Mathematically speaking, the contribution of this paper is: to propose an abstracted model of a complex decision problem; to integrate an abstracted model of climate change in the game of interest; to conduct the complete Nash equilibrium analysis of the proposed game (existence, uniqueness, expression, quantitative analysis); to conduct a detailed numerical analysis to quantify the discussed aspects such as the impact of cross-country imitation on the atmospheric global temperature in 2100.
{"title":"On the impact of cross-country imitation on climate change: A game-theoretical analysis","authors":"Bouchra Mroué , Anthony Couthures , Samson Lasaulce , Irinel-Constantin Morărescu","doi":"10.1016/j.ifacsc.2025.100309","DOIUrl":"10.1016/j.ifacsc.2025.100309","url":null,"abstract":"<div><div>As far as climate change is concerned, a recurrent question that is asked either at the government or a consumer level is: Why should I make efforts to reduce my CO<span><math><msub><mrow></mrow><mrow><mtext>2</mtext></mrow></msub></math></span> emission levels whereas the others will not make these efforts? The present paper provides qualitative elements to this question when asked at the government level. More precisely, we assume that each country wants to maximize a tradeoff between an individual benefit brought by emitting CO<span><math><msub><mrow></mrow><mrow><mtext>2</mtext></mrow></msub></math></span> and an economical damage due to climate change while being influenced by the reduction strategies of the other countries. The influence term is key for the analysis and enables more virtuous or cooperative behavior. Mathematically speaking, the contribution of this paper is: to propose an abstracted model of a complex decision problem; to integrate an abstracted model of climate change in the game of interest; to conduct the complete Nash equilibrium analysis of the proposed game (existence, uniqueness, expression, quantitative analysis); to conduct a detailed numerical analysis to quantify the discussed aspects such as the impact of cross-country imitation on the atmospheric global temperature in 2100.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100309"},"PeriodicalIF":1.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143891943","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 : 2025-04-24DOI: 10.1016/j.ifacsc.2025.100310
Addie Irawan, Mohd Helmi Suid, R.M.T. Raja Ismail, Mohd Falfazli Mat Jusof, Mohd Iskandar Putra Azahar, Ahmad Nor Kasruddin Nasir
This paper addresses the challenge of enhancing pressure regulation in pneumatic servo systems, specifically for proportional valve-controlled double-acting pneumatic cylinders (PPVDC). A Hybrid Nonlinear Sine Cosine Algorithm (HNSCA) is proposed to optimize a Finite-Time Prescribed Performance Control (FT-PPC) integrated with a PID controller. The HNSCA combines the Nonlinear Sine Cosine Algorithm (NSCA) with Adaptive Safe Experimentation Dynamics (ASED) to fine-tune FT-PPC-PID parameters, achieving rapid transient response and system stability. Simulation results demonstrate significant improvements over other optimization variants like ESCA and ASCA, including a 96% faster rise time, 61.9% reduction in settling time, and 6.4% lower overshoot. Additionally, HNSCA reduced pressure oscillations by 25%–30%, lowered power consumption by 20%–30%, and achieved up to a 50% reduction in energy consumption under a 10 kg load. It also enhanced subsonic flow stability by 10%–15% under choked flow conditions. These advancements offer practical benefits for industries utilizing pneumatic systems, such as manufacturing and robotics, by providing more precise control, reducing energy costs, and extending equipment lifespan. The findings highlight the effectiveness of the proposed approach in error minimization and long-term stability for pneumatic servo systems.
{"title":"Hybrid adaptive Sine Cosine Algorithm with Finite-Time Prescribed Performance PID Control for pneumatic servo systems","authors":"Addie Irawan, Mohd Helmi Suid, R.M.T. Raja Ismail, Mohd Falfazli Mat Jusof, Mohd Iskandar Putra Azahar, Ahmad Nor Kasruddin Nasir","doi":"10.1016/j.ifacsc.2025.100310","DOIUrl":"10.1016/j.ifacsc.2025.100310","url":null,"abstract":"<div><div>This paper addresses the challenge of enhancing pressure regulation in pneumatic servo systems, specifically for proportional valve-controlled double-acting pneumatic cylinders (PPVDC). A Hybrid Nonlinear Sine Cosine Algorithm (HNSCA) is proposed to optimize a Finite-Time Prescribed Performance Control (FT-PPC) integrated with a PID controller. The HNSCA combines the Nonlinear Sine Cosine Algorithm (NSCA) with Adaptive Safe Experimentation Dynamics (ASED) to fine-tune FT-PPC-PID parameters, achieving rapid transient response and system stability. Simulation results demonstrate significant improvements over other optimization variants like ESCA and ASCA, including a 96% faster rise time, 61.9% reduction in settling time, and 6.4% lower overshoot. Additionally, HNSCA reduced pressure oscillations by 25%–30%, lowered power consumption by 20%–30%, and achieved up to a 50% reduction in energy consumption under a 10 kg load. It also enhanced subsonic flow stability by 10%–15% under choked flow conditions. These advancements offer practical benefits for industries utilizing pneumatic systems, such as manufacturing and robotics, by providing more precise control, reducing energy costs, and extending equipment lifespan. The findings highlight the effectiveness of the proposed approach in error minimization and long-term stability for pneumatic servo systems.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100310"},"PeriodicalIF":1.8,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878484","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 : 2025-04-22DOI: 10.1016/j.ifacsc.2025.100311
Haci Mehmet Guzey
This paper proposes a federated control framework for the optimal regulation of interconnected smart grids. Unlike conventional centralized strategies, which require extensive data sharing from all nodes, our method preserves privacy by letting each local subsystem solve its own Riccati equation, generating control signals independently while sharing only minimal updates with a central aggregator. The aggregator then refines these partial solutions using the full system model, achieving near-optimal performance without disclosing sensitive local measurements. We also develop a hybrid control mechanism that dynamically switches trust factors for nodes under cyber attack, ensuring stability and resilience even in strongly coupled conditions.
Simulation results demonstrate that our federated approach yields cost performance comparable to a fully centralized LQR design, yet operates with significantly lower communication overhead. Moreover, the hybrid controller effectively mitigates cyber intrusions, preventing single-node compromises from destabilizing the entire grid. Hence, the proposed scheme addresses pressing challenges in modern smart grids – namely data privacy, cyber resilience, and scalability – while retaining the benefits of global coordination. In addition to linearized dynamics, future extensions will focus on nonlinear systems and advanced privacy-preserving protocols, paving the way for robust, next-generation energy networks.
{"title":"Federated optimal control of interconnected smart grids","authors":"Haci Mehmet Guzey","doi":"10.1016/j.ifacsc.2025.100311","DOIUrl":"10.1016/j.ifacsc.2025.100311","url":null,"abstract":"<div><div>This paper proposes a <em>federated control framework</em> for the optimal regulation of interconnected smart grids. Unlike conventional centralized strategies, which require extensive data sharing from all nodes, our method preserves privacy by letting each local subsystem solve its own Riccati equation, generating control signals independently while sharing only minimal updates with a central aggregator. The aggregator then refines these partial solutions using the full system model, achieving near-optimal performance without disclosing sensitive local measurements. We also develop a <em>hybrid control</em> mechanism that dynamically switches trust factors for nodes under cyber attack, ensuring stability and resilience even in strongly coupled conditions.</div><div>Simulation results demonstrate that our federated approach yields cost performance comparable to a fully centralized LQR design, yet operates with significantly lower communication overhead. Moreover, the hybrid controller effectively mitigates cyber intrusions, preventing single-node compromises from destabilizing the entire grid. Hence, the proposed scheme addresses pressing challenges in modern smart grids – namely data privacy, cyber resilience, and scalability – while retaining the benefits of global coordination. In addition to linearized dynamics, future extensions will focus on <em>nonlinear</em> systems and advanced privacy-preserving protocols, paving the way for robust, next-generation energy networks.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100311"},"PeriodicalIF":1.8,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860296","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 : 2025-04-16DOI: 10.1016/j.ifacsc.2025.100307
Bao-Zhu Guo , Wen-Qing Wei
In this paper, we investigate the uniform convergence of a semi-discrete scheme for output regulation of a system governed by a one-dimensional wave equation. The disturbances and reference signals stem from an exosystem, infiltrating the system through all channels. The exponential convergence of the continuous partial differential equation (PDE) system is firstly established using the Lyapunov functional approach. Utilizing the order reduction approach, we develop a semi-discrete finite difference scheme for the continuous PDE closed-loop system and demonstrate that this semi-discrete scheme exhibits uniform internal exponential stability, regardless of the step size, in complete alignment with its PDE counterpart. Consequently, the tracking errors for the discrete systems exhibit uniform exponential convergence.
{"title":"Uniform convergence of semi-discrete scheme for output regulation of 1-D wave equation","authors":"Bao-Zhu Guo , Wen-Qing Wei","doi":"10.1016/j.ifacsc.2025.100307","DOIUrl":"10.1016/j.ifacsc.2025.100307","url":null,"abstract":"<div><div>In this paper, we investigate the uniform convergence of a semi-discrete scheme for output regulation of a system governed by a one-dimensional wave equation. The disturbances and reference signals stem from an exosystem, infiltrating the system through all channels. The exponential convergence of the continuous partial differential equation (PDE) system is firstly established using the Lyapunov functional approach. Utilizing the order reduction approach, we develop a semi-discrete finite difference scheme for the continuous PDE closed-loop system and demonstrate that this semi-discrete scheme exhibits uniform internal exponential stability, regardless of the step size, in complete alignment with its PDE counterpart. Consequently, the tracking errors for the discrete systems exhibit uniform exponential convergence.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100307"},"PeriodicalIF":1.8,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848150","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 : 2025-04-08DOI: 10.1016/j.ifacsc.2025.100306
Marco Moran-Armenta , Jorge Montoya-Cháirez , Francisco G. Rossomando , Emanuel Slawiñski , Vicente Mut , Fernando A. Chicaiza , Javier Moreno-Valenzuela
This research proposes an innovative approach to improve the performance of regulation control systems in manipulators by combining PID control with gravitational compensation using neural networks. In this work, a modified PID control structure that incorporates a gravitational compensation term given by a neural network is introduced, thus allowing a more precise and adaptive response to gravitational and dynamic perturbations of the system. Furthermore, the controller’s performance is evaluated through real-time experiments in two manipulators, comparing its performance with the same structure, one without integral action, another without neural compensation and the last one assuming that the gravity vector is known. The results show a significant improvement in system regulation accuracy, demonstrating the proposed controller’s effectiveness.
{"title":"Neural networks meet PID control: Revolutionizing manipulator regulation with gravitational compensation","authors":"Marco Moran-Armenta , Jorge Montoya-Cháirez , Francisco G. Rossomando , Emanuel Slawiñski , Vicente Mut , Fernando A. Chicaiza , Javier Moreno-Valenzuela","doi":"10.1016/j.ifacsc.2025.100306","DOIUrl":"10.1016/j.ifacsc.2025.100306","url":null,"abstract":"<div><div>This research proposes an innovative approach to improve the performance of regulation control systems in manipulators by combining PID control with gravitational compensation using neural networks. In this work, a modified PID control structure that incorporates a gravitational compensation term given by a neural network is introduced, thus allowing a more precise and adaptive response to gravitational and dynamic perturbations of the system. Furthermore, the controller’s performance is evaluated through real-time experiments in two manipulators, comparing its performance with the same structure, one without integral action, another without neural compensation and the last one assuming that the gravity vector is known. The results show a significant improvement in system regulation accuracy, demonstrating the proposed controller’s effectiveness.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100306"},"PeriodicalIF":1.8,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829295","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 : 2025-03-29DOI: 10.1016/j.ifacsc.2025.100305
Ahmed Kamel, Ramin Esmzad, Nariman Niknejad, Hamidreza Modares
Balancing the trade-off between venturing into unknowns (exploration for learning) and optimizing outcomes within familiar grounds (exploitation for performance delivery) is a longstanding challenge in learning-enabled control systems. This is specifically challenging when the learning process starts with no data and rich data must be collected from the closed-loop system. This is in sharp contrast to the standard practice in data-driven control that assumes the availability of a priori rich collected open-loop data. To ensure that the closed-loop system delivers acceptable performance despite exploration for rich data collection in the context of linear quadratic regulator (LQR), we first formalize a linear matrix inequality (LMI) solution for an LQR problem that is regularized by the control entropy. Given available side information (e.g., a set that system parameters belong to), a conservative solution to the LQR can be found. To reduce the conservatism over time while ensuring an acceptable performance during learning, we present a set membership closed-loop system identification and integrate it with side information in solving the entropy-regularized LQR through Schur complement, along with the lossy S-procedure. We show that the presented set membership approach progressively improves the entropy-regularized LQR cost by shrinking the size of the set of system parameters. We also show that this is achieved while guaranteeing acceptable performance. An iterative algorithm is presented using the closed-loop set membership learning to progressively learn a new improved controller after every online data sample is collected by applying the current learned control policy. Simulation examples are provided to verify the effectiveness of the presented results.
{"title":"Robust adaptive maximum-entropy linear quadratic regulator","authors":"Ahmed Kamel, Ramin Esmzad, Nariman Niknejad, Hamidreza Modares","doi":"10.1016/j.ifacsc.2025.100305","DOIUrl":"10.1016/j.ifacsc.2025.100305","url":null,"abstract":"<div><div>Balancing the trade-off between venturing into unknowns (exploration for learning) and optimizing outcomes within familiar grounds (exploitation for performance delivery) is a longstanding challenge in learning-enabled control systems. This is specifically challenging when the learning process starts with no data and rich data must be collected from the closed-loop system. This is in sharp contrast to the standard practice in data-driven control that assumes the availability of a priori rich collected open-loop data. To ensure that the closed-loop system delivers acceptable performance despite exploration for rich data collection in the context of linear quadratic regulator (LQR), we first formalize a linear matrix inequality (LMI) solution for an LQR problem that is regularized by the control entropy. Given available side information (e.g., a set that system parameters belong to), a conservative solution to the LQR can be found. To reduce the conservatism over time while ensuring an acceptable performance during learning, we present a set membership closed-loop system identification and integrate it with side information in solving the entropy-regularized LQR through Schur complement, along with the lossy S-procedure. We show that the presented set membership approach progressively improves the entropy-regularized LQR cost by shrinking the size of the set of system parameters. We also show that this is achieved while guaranteeing acceptable performance. An iterative algorithm is presented using the closed-loop set membership learning to progressively learn a new improved controller after every online data sample is collected by applying the current learned control policy. Simulation examples are provided to verify the effectiveness of the presented results.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100305"},"PeriodicalIF":1.8,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739293","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}
Solar photovoltaic (PV) and wind energy systems (WESs) are essential for sustainable power generation, yet their performance is hindered by dynamic environmental conditions and inherent non-linearities. This review comprehensively examines advancements in maximum power point tracking (MPPT) techniques, which are crucial for optimizing the efficiency of these systems. The primary goals of this study are to offer a comprehensive evaluation of different MPPT approaches such as conventional, soft computing and hybrid techniques for PV and WESs and evaluating their effectiveness under various environments; to compare these methods depend on important performance metrices including efficiency, complexity, tracking speed, accuracy, sensor requirements and efficient operation, providing a detailed analysis for practical applications; to analyse technical and economic challenges related to MPPT deployment and provide the directions for future study to improve reliability and cost effectiveness of the system by highlighting the gaps in existing studies; and to emphasize the significance of hybrid approaches to achieve enhanced accuracy and faster tracking. By providing a detailed performance analysis and discussing the strengths and weaknesses of each method, this paper aims to guide the development of more efficient and cost-effective solutions, ultimately enhancing the sustainability and reliability of renewable energy technologies.
{"title":"Global peak operation of solar photovoltaic and wind energy systems: Current trends and innovations in enhanced optimization control techniques","authors":"Saranya Pulenthirarasa , Priya Ranjan Satpathy , Vigna K. Ramachandaramurthy , Agileswari Ramasamy , Arulampalam Atputharajah , Thurga R. Radha Krishnan","doi":"10.1016/j.ifacsc.2025.100304","DOIUrl":"10.1016/j.ifacsc.2025.100304","url":null,"abstract":"<div><div>Solar photovoltaic (PV) and wind energy systems (WESs) are essential for sustainable power generation, yet their performance is hindered by dynamic environmental conditions and inherent non-linearities. This review comprehensively examines advancements in maximum power point tracking (MPPT) techniques, which are crucial for optimizing the efficiency of these systems. The primary goals of this study are to offer a comprehensive evaluation of different MPPT approaches such as conventional, soft computing and hybrid techniques for PV and WESs and evaluating their effectiveness under various environments; to compare these methods depend on important performance metrices including efficiency, complexity, tracking speed, accuracy, sensor requirements and efficient operation, providing a detailed analysis for practical applications; to analyse technical and economic challenges related to MPPT deployment and provide the directions for future study to improve reliability and cost effectiveness of the system by highlighting the gaps in existing studies; and to emphasize the significance of hybrid approaches to achieve enhanced accuracy and faster tracking. By providing a detailed performance analysis and discussing the strengths and weaknesses of each method, this paper aims to guide the development of more efficient and cost-effective solutions, ultimately enhancing the sustainability and reliability of renewable energy technologies.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100304"},"PeriodicalIF":1.8,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768578","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 : 2025-03-24DOI: 10.1016/j.ifacsc.2025.100303
Sana BenKhaled , Cédric Delattre , Bessem Bhiri , Michel Zasadzinski , Kamel Abderrahim
This paper deals with the finite-time boundedness of an important class of hybrid systems, namely piecewise affine (PWA) systems. The main results in this article are sufficient conditions for finite-time boundedness and finite-time stabilization of PWA systems. Our approach uses a Lyapunov-like function and the S-procedure to obtain these conditions which are formulated in terms of LMIs. A numerical example illustrates the effectiveness of the proposed approach.
{"title":"Finite-time boundedness of piecewise affine systems","authors":"Sana BenKhaled , Cédric Delattre , Bessem Bhiri , Michel Zasadzinski , Kamel Abderrahim","doi":"10.1016/j.ifacsc.2025.100303","DOIUrl":"10.1016/j.ifacsc.2025.100303","url":null,"abstract":"<div><div>This paper deals with the finite-time boundedness of an important class of hybrid systems, namely piecewise affine (PWA) systems. The main results in this article are sufficient conditions for finite-time boundedness and finite-time stabilization of PWA systems. Our approach uses a Lyapunov-like function and the S-procedure to obtain these conditions which are formulated in terms of LMIs. A numerical example illustrates the effectiveness of the proposed approach.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100303"},"PeriodicalIF":1.8,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683560","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 : 2025-03-20DOI: 10.1016/j.ifacsc.2025.100302
Patricio Luppi , Lautaro Braccia , David Zumoffen
This paper presents the design of a plug-in module to address the problem of controller reconfiguration in industrial processes. The proposal is based on a multi-controller switching philosophy, where the modification of an interpolation signal defines the combination of the control actions of each controller. The contribution is based on the integration of two methodologies. On the one hand, a multivariable feedback control design approach, using the concepts of control allocation and measurement combination. On the other hand, the mapping of a set of linear stabilizing controllers onto a multi-controller, based on the Q-parameter from the Youla-Kucera theory. In this context, the set of controllers can be designed independently. Moreover, the stability is guaranteed subject to an arbitrary switching between different stabilizing controllers. The procedure is evaluated by considering two relevant scenarios of control reconfiguration: 1- a complete modification of the input–output pairing, and 2- the replacement of a classical controller with a new advanced control strategy. Based on the computational simulation of two case studies from the literature, it is shown that the plug-in module carries out the reconfiguration of the control structure, improving the dynamic performance and ensuring the stability of the system. The design is based on the nominal controller, which is not modified during the reconfiguration process. In addition, it can be easily implemented online, connected to input–output terminals of the existing controller.
{"title":"Plug-in module for controller reconfiguration based on latent variables and the Youla-Kucera parameterization","authors":"Patricio Luppi , Lautaro Braccia , David Zumoffen","doi":"10.1016/j.ifacsc.2025.100302","DOIUrl":"10.1016/j.ifacsc.2025.100302","url":null,"abstract":"<div><div>This paper presents the design of a plug-in module to address the problem of controller reconfiguration in industrial processes. The proposal is based on a multi-controller switching philosophy, where the modification of an interpolation signal defines the combination of the control actions of each controller. The contribution is based on the integration of two methodologies. On the one hand, a multivariable feedback control design approach, using the concepts of control allocation and measurement combination. On the other hand, the mapping of a set of linear stabilizing controllers onto a multi-controller, based on the Q-parameter from the Youla-Kucera theory. In this context, the set of controllers can be designed independently. Moreover, the stability is guaranteed subject to an arbitrary switching between different stabilizing controllers. The procedure is evaluated by considering two relevant scenarios of control reconfiguration: 1- a complete modification of the input–output pairing, and 2- the replacement of a classical controller with a new advanced control strategy. Based on the computational simulation of two case studies from the literature, it is shown that the plug-in module carries out the reconfiguration of the control structure, improving the dynamic performance and ensuring the stability of the system. The design is based on the nominal controller, which is not modified during the reconfiguration process. In addition, it can be easily implemented online, connected to input–output terminals of the existing controller.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100302"},"PeriodicalIF":1.8,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698000","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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