Pub Date : 2025-11-01Epub Date: 2025-07-29DOI: 10.1016/j.nahs.2025.101622
O.L.V. Costa , F. Dufour , A. Genadot
The main goal of this paper is to present a non-stationary value iteration scheme for the adaptive average control of Piecewise Deterministic Markov Processes (PDMPs), introduced by M.H.A. Davis in Davis (1984, 1993) as a family of continuous-time Markov processes punctuated by random jumps and with inter-jump movement driven by a deterministic flow. It is assumed in this paper that there are no boundary jumps. We study the adaptive average optimal control problem of PDMPs, considering that the jump intensity , the post-jump transition kernel , as well as the cost depend on an unknown parameter . For a sequence of strongly consistent estimators of (that is, converge to almost surely) a non-stationary value iteration (depending on the current estimate ) is shown to be optimal for the long-run average control problem. We assume a total variation norm condition on the parameters and of the process (which generalizes the minorization condition considered in Costa, Dufour and Genadot (2024), resulting in a span-contraction operator. The paper concludes with a numerical example.
{"title":"Non-stationary value iteration for adaptive average control of piecewise deterministic Markov processes","authors":"O.L.V. Costa , F. Dufour , A. Genadot","doi":"10.1016/j.nahs.2025.101622","DOIUrl":"10.1016/j.nahs.2025.101622","url":null,"abstract":"<div><div>The main goal of this paper is to present a non-stationary value iteration scheme for the adaptive average control of Piecewise Deterministic Markov Processes (PDMPs), introduced by M.H.A. Davis in Davis (1984, 1993) as a family of continuous-time Markov processes punctuated by random jumps and with inter-jump movement driven by a deterministic flow. It is assumed in this paper that there are no boundary jumps. We study the adaptive average optimal control problem of PDMPs, considering that the jump intensity <span><math><mi>λ</mi></math></span>, the post-jump transition kernel <span><math><mi>Q</mi></math></span>, as well as the cost <span><math><mi>C</mi></math></span> depend on an unknown parameter <span><math><msup><mrow><mi>β</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span>. For a sequence of strongly consistent estimators <span><math><mrow><mo>{</mo><msubsup><mrow><mi>β</mi></mrow><mrow><mi>n</mi></mrow><mrow><mo>∗</mo></mrow></msubsup><mo>}</mo></mrow></math></span> of <span><math><msup><mrow><mi>β</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span> (that is, <span><math><msubsup><mrow><mi>β</mi></mrow><mrow><mi>n</mi></mrow><mrow><mo>∗</mo></mrow></msubsup></math></span> converge to <span><math><msup><mrow><mi>β</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span> almost surely) a non-stationary value iteration (depending on the current estimate <span><math><msubsup><mrow><mi>β</mi></mrow><mrow><mi>n</mi></mrow><mrow><mo>∗</mo></mrow></msubsup></math></span>) is shown to be optimal for the long-run average control problem. We assume a total variation norm condition on the parameters <span><math><mi>λ</mi></math></span> and <span><math><mi>Q</mi></math></span> of the process (which generalizes the minorization condition considered in Costa, Dufour and Genadot (2024), resulting in a span-contraction operator. The paper concludes with a numerical example.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"58 ","pages":"Article 101622"},"PeriodicalIF":3.7,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01Epub Date: 2025-05-30DOI: 10.1016/j.nahs.2025.101607
B.C. van Huijgevoort , M.H.W. Engelaar , S. Soudjani , S. Haesaert
We present SySCoRe 2.0, a MATLAB toolset that synthesizes controllers for stochastic systems to satisfy temporal logic specifications. Starting from a system description and a co-safe temporal logic specification, SySCoRe provides all necessary functions for synthesizing a robust controller and quantifying the associated formal robustness guarantees. It distinguishes itself from other available tools by supporting both stochastic model order reduction techniques and space discretizations, and by being applicable to nonlinear dynamics and complex co-safe temporal logic specifications over infinite horizons. To achieve this, SySCoRe generates a finite abstraction from a possibly reduced-order version of the provided model and performs probabilistic model checking. Then, it establishes a probabilistic coupling between the original model and its finite abstraction encoded in an approximate simulation relation, based on which a lower bound on the satisfaction probability is computed. The error computed by SySCoRe does not grow linearly in the horizon of the specification, thus it provides non-trivial lower bounds for infinite-horizon specifications and unbounded disturbances. SySCoRe exploits a tensor representation to facilitate an efficient computation of transition probabilities in the finite abstraction. We showcase these features on several benchmarks and compare the performance of the toolset with existing tools and with the previous version of SySCoRe.
{"title":"SySCoRe 2.0: Toolset for formal control synthesis of continuous-state stochastic systems and temporal logic specifications","authors":"B.C. van Huijgevoort , M.H.W. Engelaar , S. Soudjani , S. Haesaert","doi":"10.1016/j.nahs.2025.101607","DOIUrl":"10.1016/j.nahs.2025.101607","url":null,"abstract":"<div><div>We present <span>SySCoRe</span> 2.0, a <span>MATLAB</span> toolset that synthesizes controllers for stochastic systems to satisfy temporal logic specifications. Starting from a system description and a co-safe temporal logic specification, <span>SySCoRe</span> provides all necessary functions for synthesizing a robust controller and quantifying the associated formal robustness guarantees. It distinguishes itself from other available tools by supporting both stochastic model order reduction techniques and space discretizations, and by being applicable to nonlinear dynamics and complex co-safe temporal logic specifications over infinite horizons. To achieve this, <span>SySCoRe</span> generates a finite abstraction from a possibly reduced-order version of the provided model and performs probabilistic model checking. Then, it establishes a probabilistic coupling between the original model and its finite abstraction encoded in an approximate simulation relation, based on which a lower bound on the satisfaction probability is computed. The error computed by <span>SySCoRe</span> does not grow linearly in the horizon of the specification, thus it provides non-trivial lower bounds for infinite-horizon specifications and unbounded disturbances. <span>SySCoRe</span> exploits a tensor representation to facilitate an efficient computation of transition probabilities in the finite abstraction. We showcase these features on several benchmarks and compare the performance of the toolset with existing tools and with the previous version of <span>SySCoRe</span>.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"58 ","pages":"Article 101607"},"PeriodicalIF":3.7,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 paper is about state estimation in a timed probabilistic setting. A reference model, namely a labeled timed probabilistic automaton, is used for this purpose and an a posteriori probability vector is defined based on a sequence of observations and their associated time stamps that have been collected thus far. The observable language of the considered system is assumed to be live. The main contribution of the paper is to introduce and characterize some basic detectability notions for timed stochastic systems: (i) event detectability, which implies that the system becomes detectable at the time instant of each new observation but may lose the detectability property between two observations, and (ii) silent detectability, which implies that the system becomes detectable when no observation is collected within an arbitrary large duration. Relaxed notions of detectability are also studied: first, assuming that, given a threshold, the a priori probability that an observed timed sequence leads to an exact reconstruction of the state, is larger than or equal to that threshold; second, by replacing the estimation of single states by the estimation of classes formed by several states.
{"title":"Detectability notions for a class of finite labeled Markovian systems","authors":"Dimitri Lefebvre , Carla Seatzu , Christoforos N. Hadjicostis , Alessandro Giua","doi":"10.1016/j.nahs.2025.101586","DOIUrl":"10.1016/j.nahs.2025.101586","url":null,"abstract":"<div><div>This paper is about state estimation in a timed probabilistic setting. A reference model, namely a labeled timed probabilistic automaton, is used for this purpose and an a posteriori probability vector is defined based on a sequence of observations and their associated time stamps that have been collected thus far. The observable language of the considered system is assumed to be live. The main contribution of the paper is to introduce and characterize some basic detectability notions for timed stochastic systems: (i) <em>event detectability</em>, which implies that the system becomes detectable at the time instant of each new observation but may lose the detectability property between two observations, and (ii) <em>silent detectability</em>, which implies that the system becomes detectable when no observation is collected within an arbitrary large duration. Relaxed notions of detectability are also studied: first, assuming that, given a threshold, the a priori probability that an observed timed sequence leads to an exact reconstruction of the state, is larger than or equal to that threshold; second, by replacing the estimation of single states by the estimation of classes formed by several states.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101586"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-04-28DOI: 10.1016/j.nahs.2025.101602
Marco Florentino , Tiago Carvalho
In this paper we establish conditions in order to obtain a set of trajectories of -dimensional piecewise smooth vector fields that preserves measure even in the case where sliding motion is allowed. The key hypothesis is the occurrence of a sliding–escaping connection. As consequence, classical results from the ergodic theory of dynamical systems can be adapted for the context of piecewise smooth vector fields, just as the Poincaré’s Recurrence Theorem and the Birkhoff’s Theorem. Also, we apply the results for previous models of the literature.
{"title":"Piecewise smooth vector fields with sliding motion preserving measure","authors":"Marco Florentino , Tiago Carvalho","doi":"10.1016/j.nahs.2025.101602","DOIUrl":"10.1016/j.nahs.2025.101602","url":null,"abstract":"<div><div>In this paper we establish conditions in order to obtain a set of trajectories of <span><math><mi>n</mi></math></span>-dimensional piecewise smooth vector fields that preserves measure even in the case where sliding motion is allowed. The key hypothesis is the occurrence of a sliding–escaping connection. As consequence, classical results from the ergodic theory of dynamical systems can be adapted for the context of piecewise smooth vector fields, just as the Poincaré’s Recurrence Theorem and the Birkhoff’s Theorem. Also, we apply the results for previous models of the literature.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101602"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-15DOI: 10.1016/j.nahs.2025.101601
Aili Fan , Lin Du , Junmin Li , Yuhua Du , Zichen Deng , Jinde Cao
In this article, we mainly address the function matrix projective synchronization (FMPS) problem with prescribed performance (PP) between a drive network (DN) with time-varying uncertain coupling, and its corresponding response network (RN) with mismatched dimensions. A new hybrid adaptive learning law is proposed, which consists of a discrete adaptive law designed for unknown time-varying coupling coefficients, and a continuous adaptive law designed for time-invariant coefficients. The proposed work extends the adaptive synchronization control that is originally applicable only with the constant coupling coefficient to the case where the coefficients are time-varying. To ensure the state trajectories of the RN are projectively synchronized to those of the DN while complying with PP constraints, a PP controller is designed. Meanwhile, to reduce the communication load, the event-triggered communication (ETC) mechanism is implemented. Finally, the effectiveness of the designed control scheme, adaptive laws and ETC protocol is validated through simulation.
{"title":"Prescribed performance projective synchronization for unknown complex networks with mismatched dimensions via event-triggered mechanism","authors":"Aili Fan , Lin Du , Junmin Li , Yuhua Du , Zichen Deng , Jinde Cao","doi":"10.1016/j.nahs.2025.101601","DOIUrl":"10.1016/j.nahs.2025.101601","url":null,"abstract":"<div><div>In this article, we mainly address the function matrix projective synchronization (FMPS) problem with prescribed performance (PP) between a drive network (DN) with time-varying uncertain coupling, and its corresponding response network (RN) with mismatched dimensions. A new hybrid adaptive learning law is proposed, which consists of a discrete adaptive law designed for unknown time-varying coupling coefficients, and a continuous adaptive law designed for time-invariant coefficients. The proposed work extends the adaptive synchronization control that is originally applicable only with the constant coupling coefficient to the case where the coefficients are time-varying. To ensure the state trajectories of the RN are projectively synchronized to those of the DN while complying with PP constraints, a PP controller is designed. Meanwhile, to reduce the communication load, the event-triggered communication (ETC) mechanism is implemented. Finally, the effectiveness of the designed control scheme, adaptive laws and ETC protocol is validated through simulation.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101601"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We consider the problem of predictive monitoring (PM), i.e., predicting at runtime the satisfaction of a desired property from the current system’s state. Due to its relevance for runtime safety assurance and online control, PM methods need to be efficient to enable timely interventions against predicted violations, while providing correctness guarantees. We introduce quantitative predictive monitoring (QPM), a PM method to support stochastic processes and rich specifications given in Signal Temporal Logic (STL). QPM provides a quantitative measure of satisfaction of some property by predicting its quantitative (a.k.a. robust) STL semantics, either spatial or temporal. QPM derives prediction intervals that are highly efficient to compute and with probabilistic guarantees, in that the intervals cover with arbitrary probability the STL robustness values relative to the stochastic evolution of the system. To do so, we take a machine-learning approach and leverage recent advances in conformal inference for quantile regression, thereby avoiding expensive Monte Carlo simulations at runtime to estimate the intervals. We also show how our monitors can be combined in a compositional manner to handle composite formulas, without retraining the predictors or sacrificing the guarantees. We further equip QPM with techniques to ensure conditional validity of the prediction intervals, i.e., such that the probabilistic guarantees hold relative to any state of the system (or any satisfaction value), thereby significantly enhancing the consistency and reliability of the resulting monitor. We demonstrate the effectiveness and scalability of QPM over a benchmark of five discrete-time stochastic processes with varying degrees of complexity, including a stochastic multi-agent system.
{"title":"Conformal quantitative predictive monitoring of stochastic systems with conditional validity","authors":"Francesca Cairoli , Tom Kuipers , Luca Bortolussi , Nicola Paoletti","doi":"10.1016/j.nahs.2025.101606","DOIUrl":"10.1016/j.nahs.2025.101606","url":null,"abstract":"<div><div>We consider the problem of predictive monitoring (PM), i.e., predicting at runtime the satisfaction of a desired property from the current system’s state. Due to its relevance for runtime safety assurance and online control, PM methods need to be efficient to enable timely interventions against predicted violations, while providing correctness guarantees. We introduce <em>quantitative predictive monitoring (QPM)</em>, a PM method to support stochastic processes and rich specifications given in Signal Temporal Logic (STL). QPM provides a quantitative measure of satisfaction of some property <span><math><mi>ϕ</mi></math></span> by predicting its quantitative (a.k.a. robust) STL semantics, either spatial or temporal. QPM derives prediction intervals that are highly efficient to compute and with probabilistic guarantees, in that the intervals cover with arbitrary probability the STL robustness values relative to the stochastic evolution of the system. To do so, we take a machine-learning approach and leverage recent advances in conformal inference for quantile regression, thereby avoiding expensive Monte Carlo simulations at runtime to estimate the intervals. We also show how our monitors can be combined in a compositional manner to handle composite formulas, without retraining the predictors or sacrificing the guarantees. We further equip QPM with techniques to ensure conditional validity of the prediction intervals, i.e., such that the probabilistic guarantees hold relative to any state of the system (or any satisfaction value), thereby significantly enhancing the consistency and reliability of the resulting monitor. We demonstrate the effectiveness and scalability of QPM over a benchmark of five discrete-time stochastic processes with varying degrees of complexity, including a stochastic multi-agent system.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101606"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-03-28DOI: 10.1016/j.nahs.2025.101596
Cuiping Lu , Xiaodi Li
This paper concentrates on stabilization problem of nonlinear delay systems involved unknown parameters via adaptive impulsive observer-based saturated control (AIOSC). Different from the existing literature that only the system state reconstruction and parameter estimation problems are comprehensively and thoroughly studied, we simultaneously solve the stabilization problem of such system itself. In virtue of an improved set inclusion relationship related to the augmented vector, the saturated effects on both impulsive correction and continuous control are explored in the sense of unmeasurable states. The main challenge of this paper is that with the help of the modified convex combination method, the time-varying Lyapunov function-based method, and comparison principle, how to fully utilize the systematic information to construct an elastic constraint relationship among system structure, delay information, and impulsive time sequence, which makes system parameters adjust appropriately as needed. Moreover, the maximum estimation of attractive domain is obtained by a convex optimal problem. And two examples are presented to demonstrate the validity of results, where stabilization of Lorenz system involved unknown parameters is considered.
{"title":"Stabilization of nonlinear delay systems: Adaptive impulsive observer-based saturated control approach","authors":"Cuiping Lu , Xiaodi Li","doi":"10.1016/j.nahs.2025.101596","DOIUrl":"10.1016/j.nahs.2025.101596","url":null,"abstract":"<div><div>This paper concentrates on stabilization problem of nonlinear delay systems involved unknown parameters via adaptive impulsive observer-based saturated control (<em>AIOSC</em>). Different from the existing literature that only the system state reconstruction and parameter estimation problems are comprehensively and thoroughly studied, we simultaneously solve the stabilization problem of such system itself. In virtue of an improved set inclusion relationship related to the augmented vector, the saturated effects on both impulsive correction and continuous control are explored in the sense of unmeasurable states. The main challenge of this paper is that with the help of the modified convex combination method, the time-varying Lyapunov function-based method, and comparison principle, how to fully utilize the systematic information to construct an elastic constraint relationship among system structure, delay information, and impulsive time sequence, which makes system parameters adjust appropriately as needed. Moreover, the maximum estimation of attractive domain is obtained by a convex optimal problem. And two examples are presented to demonstrate the validity of results, where stabilization of Lorenz system involved unknown parameters is considered.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101596"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-04-16DOI: 10.1016/j.nahs.2025.101598
Arnab Mapui, Santwana Mukhopadhyay
The main emphasis of this paper is to address the issue of event- and self-triggered impulsive control for the prescribed-time stability of impulsive systems. In the first part of the article, some Lyapunov-like sufficient conditions are derived to stabilize an impulsive system within the prescribed-time, where impulsive instants are obtained through an event-triggered mechanism. Unlike event-triggered control, event-triggered impulsive control executes solely when the event is generated. The second part of the article provides sufficient Lyapunov-like criteria for the prescribed-time stability of impulsive systems via a self-triggered mechanism. Contrary to the event-triggered impulsive control, where triggering instants are obtained through continuous or periodic monitoring of the event-triggering conditions, the proposed self-triggered impulsive control strategy can estimate the next triggering instant by the information available in the currently triggered instant. Moreover, it is demonstrated that the Zeno behavior can be excluded from both of the proposed mechanisms. Finally, two instances are provided to illustrate the theoretical results numerically and verify the veracity of the proposed methodologies.
{"title":"Lyapunov-like prescribed-time stability of impulsive systems via event & self-triggered impulsive control","authors":"Arnab Mapui, Santwana Mukhopadhyay","doi":"10.1016/j.nahs.2025.101598","DOIUrl":"10.1016/j.nahs.2025.101598","url":null,"abstract":"<div><div>The main emphasis of this paper is to address the issue of event- and self-triggered impulsive control for the prescribed-time stability of impulsive systems. In the first part of the article, some Lyapunov-like sufficient conditions are derived to stabilize an impulsive system within the prescribed-time, where impulsive instants are obtained through an event-triggered mechanism. Unlike event-triggered control, event-triggered impulsive control executes solely when the event is generated. The second part of the article provides sufficient Lyapunov-like criteria for the prescribed-time stability of impulsive systems via a self-triggered mechanism. Contrary to the event-triggered impulsive control, where triggering instants are obtained through continuous or periodic monitoring of the event-triggering conditions, the proposed self-triggered impulsive control strategy can estimate the next triggering instant by the information available in the currently triggered instant. Moreover, it is demonstrated that the Zeno behavior can be excluded from both of the proposed mechanisms. Finally, two instances are provided to illustrate the theoretical results numerically and verify the veracity of the proposed methodologies.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101598"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-20DOI: 10.1016/j.nahs.2025.101604
D.A. Deenen , E. Maljaars , L.C. Sebeke , B. de Jager , E. Heijman , H. Grüll , W.P.M.H. Heemels
A switched-actuator system with setup times (SAcSS) is a system in which the actuator configuration has to be switched during operation, and where the switching induces non-negligible actuator downtime. Optimally controlling SAcSSs requires the online solving of both a discrete actuator allocation problem, in which the switch-induced actuator downtime is taken into account, as well as an optimization problem for the (typically continuous) control inputs. Mixed-integer model predictive control (MI-MPC) offers a powerful framework for tackling such problems. However, the efficient modeling of SAcSSs for MI-MPC is not straightforward, and real-time feasibility is often a major hurdle in practice. It is the objective of this paper to provide an intuitive and systematic modeling procedure tailored to SAcSSs, which is specifically designed to allow for user-friendly controller synthesis, and to yield efficient MI-MPCs. We apply these new results in a case study of large-volume magnetic-resonance-guided high-intensity focused ultrasound hyperthermia, which involves the heating of tumors (using real-valued local heating controls, as well as discrete range-extending actuator relocation during which no heating is allowed) to enhance the efficacy of radio- and chemotherapy.
{"title":"Model predictive control of switched-actuator systems with setup times, and application to hyperthermia cancer therapies","authors":"D.A. Deenen , E. Maljaars , L.C. Sebeke , B. de Jager , E. Heijman , H. Grüll , W.P.M.H. Heemels","doi":"10.1016/j.nahs.2025.101604","DOIUrl":"10.1016/j.nahs.2025.101604","url":null,"abstract":"<div><div>A switched-actuator system with setup times (SAcSS) is a system in which the actuator configuration has to be switched during operation, and where the switching induces non-negligible actuator downtime. Optimally controlling SAcSSs requires the online solving of both a discrete actuator allocation problem, in which the switch-induced actuator downtime is taken into account, as well as an optimization problem for the (typically continuous) control inputs. Mixed-integer model predictive control (MI-MPC) offers a powerful framework for tackling such problems. However, the efficient modeling of SAcSSs for MI-MPC is not straightforward, and real-time feasibility is often a major hurdle in practice. It is the objective of this paper to provide an intuitive and systematic modeling procedure tailored to SAcSSs, which is specifically designed to allow for user-friendly controller synthesis, and to yield efficient MI-MPCs. We apply these new results in a case study of large-volume magnetic-resonance-guided high-intensity focused ultrasound hyperthermia, which involves the heating of tumors (using real-valued local heating controls, as well as discrete range-extending actuator relocation during which no heating is allowed) to enhance the efficacy of radio- and chemotherapy.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101604"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144089442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-01Epub Date: 2025-05-28DOI: 10.1016/j.nahs.2025.101609
Yafei Zhai , Fubao Xi
As a continuation of the study by Hou and Shao [Sci. China Math., 63 (2020), pp. 1169-1180], this work makes three key advances in studying state-dependent switching Cox–Ingersoll–Ross processes. First, we establish tail behavior results for stationary distributions across both finite and infinite regimes-a significant extension beyond their framework. Second, through novel auxiliary Markov chains, we explicitly construct a comparison theorem specifically adapted for state-dependent switching diffusions. Third, we derive sufficient recurrence conditions for infinite-regime cases. Our approach provides rigorous control of state-dependent switching component processes with Markov chains and remains applicable to broader classes of state-dependent switching diffusion processes.
作为侯、邵研究的延续[Sci。中国数学。， 63 (2020), pp. 1169-1180]，这项工作在研究状态依赖开关Cox-Ingersoll-Ross过程方面取得了三个关键进展。首先，我们建立了有限和无限状态下平稳分布的尾部行为结果-这是对其框架的重要扩展。其次，通过新的辅助马尔可夫链，我们明确地构造了一个特别适用于状态相关切换扩散的比较定理。第三，我们得到了无限区情形的充分递归条件。我们的方法提供了具有马尔可夫链的状态相关切换组件过程的严格控制，并且仍然适用于更广泛类别的状态相关切换扩散过程。
{"title":"The tail behavior of Cox–Ingersoll–Ross processes with state-dependent switching","authors":"Yafei Zhai , Fubao Xi","doi":"10.1016/j.nahs.2025.101609","DOIUrl":"10.1016/j.nahs.2025.101609","url":null,"abstract":"<div><div>As a continuation of the study by Hou and Shao [Sci. China Math., 63 (2020), pp. 1169-1180], this work makes three key advances in studying state-dependent switching Cox–Ingersoll–Ross processes. First, we establish tail behavior results for stationary distributions across both finite and infinite regimes-a significant extension beyond their framework. Second, through novel auxiliary Markov chains, we explicitly construct a comparison theorem specifically adapted for state-dependent switching diffusions. Third, we derive sufficient recurrence conditions for infinite-regime cases. Our approach provides rigorous control of state-dependent switching component processes with Markov chains and remains applicable to broader classes of state-dependent switching diffusion processes.</div></div>","PeriodicalId":49011,"journal":{"name":"Nonlinear Analysis-Hybrid Systems","volume":"57 ","pages":"Article 101609"},"PeriodicalIF":3.7,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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