Pub Date : 2024-12-27DOI: 10.1109/LCSYS.2024.3523432
Nguyen Thi Lien;Le Van Hien;Nguyen Nhu Thang
This note is concerned with a class of homogeneous cooperative systems with bounded time-varying delays described by the Caputo fractional derivative. We focus on the existence, uniqueness, and Mittag-Leffler stability of positive solutions when the associated vector fields are homogeneous with a degree less than or equal to one. Specifically, the solvability is first exploited through the fixed point theory, leveraging the homogeneity of nonlinear terms. Then, a delay-independent condition for Mittag-Leffler stability is established by utilizing the properties of Mittag-Leffler functions and the comparison principle. Finally, the theoretical results are validated by a given numerical example.
{"title":"Mittag-Leffler Stability of Homogeneous Fractional-Order Systems With Delay","authors":"Nguyen Thi Lien;Le Van Hien;Nguyen Nhu Thang","doi":"10.1109/LCSYS.2024.3523432","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523432","url":null,"abstract":"This note is concerned with a class of homogeneous cooperative systems with bounded time-varying delays described by the Caputo fractional derivative. We focus on the existence, uniqueness, and Mittag-Leffler stability of positive solutions when the associated vector fields are homogeneous with a degree less than or equal to one. Specifically, the solvability is first exploited through the fixed point theory, leveraging the homogeneity of nonlinear terms. Then, a delay-independent condition for Mittag-Leffler stability is established by utilizing the properties of Mittag-Leffler functions and the comparison principle. Finally, the theoretical results are validated by a given numerical example.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3243-3248"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938066","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 : 2024-12-27DOI: 10.1109/LCSYS.2024.3523845
Charlotte Cathcart;Ian Xul Belaustegui;Alessio Franci;Naomi Ehrich Leonard
We present, analyze, and illustrate a first-of-its-kind model of two-dimensional excitable (spiking) dynamics for decision-making over two options. The model, Spiking Nonlinear Opinion Dynamics (S-NOD), provides superior agility, characterized by fast, flexible, and adaptive response to rapid and unpredictable changes in context, environment, or information received about available options. S-NOD derives through the introduction of a single extra term to the previously presented Nonlinear Opinion Dynamics (NOD) for fast and flexible multi-agent decision-making behavior. The extra term is inspired by the fast-positive, slow-negative mixed-feedback structure of excitable systems. The agile behaviors brought about by the new excitable nature of decision-making driven by S-NOD are analyzed in a general setting and illustrated in an application to multi-robot navigation around human movers.
{"title":"Spiking Nonlinear Opinion Dynamics (S-NOD) for Agile Decision-Making","authors":"Charlotte Cathcart;Ian Xul Belaustegui;Alessio Franci;Naomi Ehrich Leonard","doi":"10.1109/LCSYS.2024.3523845","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523845","url":null,"abstract":"We present, analyze, and illustrate a first-of-its-kind model of two-dimensional excitable (spiking) dynamics for decision-making over two options. The model, Spiking Nonlinear Opinion Dynamics (S-NOD), provides superior agility, characterized by fast, flexible, and adaptive response to rapid and unpredictable changes in context, environment, or information received about available options. S-NOD derives through the introduction of a single extra term to the previously presented Nonlinear Opinion Dynamics (NOD) for fast and flexible multi-agent decision-making behavior. The extra term is inspired by the fast-positive, slow-negative mixed-feedback structure of excitable systems. The agile behaviors brought about by the new excitable nature of decision-making driven by S-NOD are analyzed in a general setting and illustrated in an application to multi-robot navigation around human movers.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3267-3272"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938063","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 : 2024-12-27DOI: 10.1109/LCSYS.2024.3523844
Marcelo Alves Dos Santos;Antonio Ferramosca;Guilherme Vianna Raffo
This letter analyzes the stability properties of a nonlinear Model Predictive Control (MPC) scheme for avoidance. This control approach introduces an extra penalty for avoidance within the nonlinear tracking MPC framework. We demonstrate that, under a mild assumption on the avoidance penalty, the closed-loop system is Input-to-State Stable (ISS) with respect to this penalty. Furthermore, we discuss the conditions under which asymptotic stability can be achieved and present a simplified scheme with relaxed terminal constraints. To illustrate the effectiveness of the proposed strategy, we apply it to the control of a van der Pol oscillator subjected to non-convex constraints.
{"title":"On the Stability of a Nonlinear MPC Scheme for Avoidance","authors":"Marcelo Alves Dos Santos;Antonio Ferramosca;Guilherme Vianna Raffo","doi":"10.1109/LCSYS.2024.3523844","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523844","url":null,"abstract":"This letter analyzes the stability properties of a nonlinear Model Predictive Control (MPC) scheme for avoidance. This control approach introduces an extra penalty for avoidance within the nonlinear tracking MPC framework. We demonstrate that, under a mild assumption on the avoidance penalty, the closed-loop system is Input-to-State Stable (ISS) with respect to this penalty. Furthermore, we discuss the conditions under which asymptotic stability can be achieved and present a simplified scheme with relaxed terminal constraints. To illustrate the effectiveness of the proposed strategy, we apply it to the control of a van der Pol oscillator subjected to non-convex constraints.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3285-3290"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142976168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-27DOI: 10.1109/LCSYS.2024.3523466
Giovanna Amorim;Anastasia Bizyaeva;Alessio Franci;Naomi Ehrich Leonard
We propose and analyze a nonlinear opinion dynamics model for an agent making decisions about a continuous distribution of options in the presence of input. Inspired by perceptual decision-making, we develop new theory for opinion formation in response to inputs about options distributed on the circle. Options on the circle can represent, e.g., the possible directions of perceived objects and resulting heading directions in planar robotic navigation problems. Interactions among options are encoded through a spatially invariant kernel, which we design to ensure that only a small (finite) subset of options can be favored over the continuum. We leverage the spatial invariance of the model linearization to design flexible, distributed opinion-forming behaviors using spatiotemporal frequency domain and bifurcation analysis. We illustrate our model’s versatility with an application to robotic navigation in crowded spaces.
{"title":"Spatially-Invariant Opinion Dynamics on the Circle","authors":"Giovanna Amorim;Anastasia Bizyaeva;Alessio Franci;Naomi Ehrich Leonard","doi":"10.1109/LCSYS.2024.3523466","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523466","url":null,"abstract":"We propose and analyze a nonlinear opinion dynamics model for an agent making decisions about a continuous distribution of options in the presence of input. Inspired by perceptual decision-making, we develop new theory for opinion formation in response to inputs about options distributed on the circle. Options on the circle can represent, e.g., the possible directions of perceived objects and resulting heading directions in planar robotic navigation problems. Interactions among options are encoded through a spatially invariant kernel, which we design to ensure that only a small (finite) subset of options can be favored over the continuum. We leverage the spatial invariance of the model linearization to design flexible, distributed opinion-forming behaviors using spatiotemporal frequency domain and bifurcation analysis. We illustrate our model’s versatility with an application to robotic navigation in crowded spaces.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3231-3236"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938065","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 : 2024-12-27DOI: 10.1109/LCSYS.2024.3523584
Ryotaro Shima;Yuji Ito;Tatsuya Miyano
This letter analyzes the contraction property of the nonlinear systems controlled by suboptimal model predictive control (MPC) using the continuation method. We propose a contraction metric that reflects the hierarchical dynamics inherent in the continuation method. We derive a pair of matrix inequalities that elucidate the impact of suboptimality on the contraction of the optimally controlled closed-loop system. A numerical example is presented to verify our contraction analysis. Our results are applicable to other MPCs than stabilization, including economic MPC.
{"title":"Contraction Analysis of Continuation Method for Suboptimal Model Predictive Control","authors":"Ryotaro Shima;Yuji Ito;Tatsuya Miyano","doi":"10.1109/LCSYS.2024.3523584","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523584","url":null,"abstract":"This letter analyzes the contraction property of the nonlinear systems controlled by suboptimal model predictive control (MPC) using the continuation method. We propose a contraction metric that reflects the hierarchical dynamics inherent in the continuation method. We derive a pair of matrix inequalities that elucidate the impact of suboptimality on the contraction of the optimally controlled closed-loop system. A numerical example is presented to verify our contraction analysis. Our results are applicable to other MPCs than stabilization, including economic MPC.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3261-3266"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817557","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-27DOI: 10.1109/LCSYS.2024.3523385
Teo Brandt;Rafael Fierro;Claus Danielson
This letter extends the application of the invariant set motion planner (ISMP) to space vehicles operating in $mathbb {SE}text {(}3text {)} = mathbb {SO}text {(}3text {)} rtimes {mathbb {R}}^{3}$ , considering the quaternion representation of $mathbb {SO}text {(}3text {)}$ . We provide a proof for a collision-free set by extending the concepts of configuration-space bubbles from robotics literature. We derive a constraint admissible positive invariant (CAPI) subset within the configuration-space bubble for a robust linearization of the nonlinear vehicle dynamics. The motion planner constructs a directed graph of position and orientation equilibria covering $mathbb {SE}text {(}3text {)}$ . CAPI sets are constructed to verify that equilibria are connected by a feasible trajectory. Graph search is applied to determine a sequence of reference configurations, starting at an initial position-orientation and terminating at a goal position-orientation. Simulation results are included that demonstrate the safe navigation of a vehicle in the presence of an obstacle. The trajectory is shown to maintain the CAPI conditions and is therefore safe under the nonlinear translational and rotational closed-loop vehicle dynamics.
{"title":"Safe Vehicle Motion Planning Using Constraint Admissible Positive Invariant Sets on SE(3)","authors":"Teo Brandt;Rafael Fierro;Claus Danielson","doi":"10.1109/LCSYS.2024.3523385","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523385","url":null,"abstract":"This letter extends the application of the invariant set motion planner (ISMP) to space vehicles operating in <inline-formula> <tex-math>$mathbb {SE}text {(}3text {)} = mathbb {SO}text {(}3text {)} rtimes {mathbb {R}}^{3}$ </tex-math></inline-formula>, considering the quaternion representation of <inline-formula> <tex-math>$mathbb {SO}text {(}3text {)}$ </tex-math></inline-formula>. We provide a proof for a collision-free set by extending the concepts of configuration-space bubbles from robotics literature. We derive a constraint admissible positive invariant (CAPI) subset within the configuration-space bubble for a robust linearization of the nonlinear vehicle dynamics. The motion planner constructs a directed graph of position and orientation equilibria covering <inline-formula> <tex-math>$mathbb {SE}text {(}3text {)}$ </tex-math></inline-formula>. CAPI sets are constructed to verify that equilibria are connected by a feasible trajectory. Graph search is applied to determine a sequence of reference configurations, starting at an initial position-orientation and terminating at a goal position-orientation. Simulation results are included that demonstrate the safe navigation of a vehicle in the presence of an obstacle. The trajectory is shown to maintain the CAPI conditions and is therefore safe under the nonlinear translational and rotational closed-loop vehicle dynamics.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3255-3260"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142975928","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 : 2024-12-27DOI: 10.1109/LCSYS.2024.3523843
Dipankar Maity;Arman Pourghorban
We consider a variant of the target defense problems where a group of defenders are tasked to simultaneously capture an intruder. The intruder’s objective is to reach a target without being simultaneously captured by the defender team. Some of the defenders are sensing-limited and do not have any information regarding the intruder’s position or velocity at any time. The defenders may communicate with each other using a connected communication graph. We propose a decentralized feedback strategy for the defenders, which transforms the simultaneous capture problem into a nonlinear consensus problem. We derive a sufficient condition for simultaneous capture in terms of the agents’ speeds, sensing, and communication capabilities. The proposed decentralized controller is evaluated through extensive numerical simulations.
{"title":"Cooperative Target Defense Under Communication and Sensing Constraints","authors":"Dipankar Maity;Arman Pourghorban","doi":"10.1109/LCSYS.2024.3523843","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523843","url":null,"abstract":"We consider a variant of the target defense problems where a group of defenders are tasked to simultaneously capture an intruder. The intruder’s objective is to reach a target without being simultaneously captured by the defender team. Some of the defenders are sensing-limited and do not have any information regarding the intruder’s position or velocity at any time. The defenders may communicate with each other using a connected communication graph. We propose a decentralized feedback strategy for the defenders, which transforms the simultaneous capture problem into a nonlinear consensus problem. We derive a sufficient condition for simultaneous capture in terms of the agents’ speeds, sensing, and communication capabilities. The proposed decentralized controller is evaluated through extensive numerical simulations.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3321-3326"},"PeriodicalIF":2.4,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184231","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 : 2024-12-26DOI: 10.1109/LCSYS.2024.3522594
Xu Shang;Jorge Cortés;Yang Zheng
Koopman operator theory and Willems’ fundamental lemma both can provide (approximated) data-driven linear representation for nonlinear systems. However, choosing lifting functions for the Koopman operator is challenging, and the quality of the data-driven model from Willems’ fundamental lemma has no guarantee for general nonlinear systems. In this letter, we extend Willems’ fundamental lemma for a class of nonlinear systems that admit a Koopman linear embedding. We first characterize the relationship between the trajectory space of a nonlinear system and that of its Koopman linear embedding. We then prove that the trajectory space of Koopman linear embedding can be formed by a linear combination of rich-enough trajectories from the nonlinear system. Combining these two results leads to a data-driven representation of the nonlinear system, which bypasses the need for the lifting functions and thus eliminates the associated bias errors. Our results illustrate that both the width (more trajectories) and depth (longer trajectories) of the trajectory library are important to ensure the accuracy of the data-driven model.
{"title":"Willems’ Fundamental Lemma for Nonlinear Systems With Koopman Linear Embedding","authors":"Xu Shang;Jorge Cortés;Yang Zheng","doi":"10.1109/LCSYS.2024.3522594","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3522594","url":null,"abstract":"Koopman operator theory and Willems’ fundamental lemma both can provide (approximated) data-driven linear representation for nonlinear systems. However, choosing lifting functions for the Koopman operator is challenging, and the quality of the data-driven model from Willems’ fundamental lemma has no guarantee for general nonlinear systems. In this letter, we extend Willems’ fundamental lemma for a class of nonlinear systems that admit a Koopman linear embedding. We first characterize the relationship between the trajectory space of a nonlinear system and that of its Koopman linear embedding. We then prove that the trajectory space of Koopman linear embedding can be formed by a linear combination of rich-enough trajectories from the nonlinear system. Combining these two results leads to a data-driven representation of the nonlinear system, which bypasses the need for the lifting functions and thus eliminates the associated bias errors. Our results illustrate that both the width (more trajectories) and depth (longer trajectories) of the trajectory library are important to ensure the accuracy of the data-driven model.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3135-3140"},"PeriodicalIF":2.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142962894","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 : 2024-12-26DOI: 10.1109/LCSYS.2024.3523244
Hanwen Cai;Weiyao Lan;Xiao Yu
This letter addresses the semi-global output regulation problem for continuous-time linear systems with input saturation and unknown dynamics. First, we employ a low-gain technique to design a state-feedback linear control law such that the control input operates within the linear region of the actuator. Then, taking it as the linear part, we construct a composite nonlinear feedback (CNF) control law, consisting of both linear and nonlinear parts, to improve the transient performance of the closed-loop system. Without requiring prior knowledge of the system dynamics or an initial stabilizing control policy, we propose a novel adaptive dynamic programming (ADP) learning algorithm. This algorithm learns both the linear part and the nonlinear part of the CNF control law using the same set of data. In addition, the algorithm uses single-layer filters, eliminating the need for integral operations during the learning process. Finally, the effectiveness of the proposed algorithm is demonstrated by an illustrative example.
{"title":"Data-Driven Composite Nonlinear Feedback Control for Semi-Global Output Regulation of Unknown Linear Systems With Input Saturation","authors":"Hanwen Cai;Weiyao Lan;Xiao Yu","doi":"10.1109/LCSYS.2024.3523244","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3523244","url":null,"abstract":"This letter addresses the semi-global output regulation problem for continuous-time linear systems with input saturation and unknown dynamics. First, we employ a low-gain technique to design a state-feedback linear control law such that the control input operates within the linear region of the actuator. Then, taking it as the linear part, we construct a composite nonlinear feedback (CNF) control law, consisting of both linear and nonlinear parts, to improve the transient performance of the closed-loop system. Without requiring prior knowledge of the system dynamics or an initial stabilizing control policy, we propose a novel adaptive dynamic programming (ADP) learning algorithm. This algorithm learns both the linear part and the nonlinear part of the CNF control law using the same set of data. In addition, the algorithm uses single-layer filters, eliminating the need for integral operations during the learning process. Finally, the effectiveness of the proposed algorithm is demonstrated by an illustrative example.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3225-3230"},"PeriodicalIF":2.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938061","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 : 2024-12-26DOI: 10.1109/LCSYS.2024.3522949
Ryoma Yasunaga;Yorie Nakahira;Yutaka Hori
Quantifying long-term risk in large-scale multi-agent systems is critical for ensuring safe operation. However, the high dimensionality of these systems and the rarity of risk events can make the required computations prohibitively expensive. To overcome this challenge, we introduce a graph-based representation and efficient risk quantification techniques tailored for stochastic multi-agent systems. A key technical innovation is a systematic approach to decompose the estimation problem of system-wide safety probabilities into smaller, lower-dimensional sub-systems with sub-safe sets. This decomposition leverages the graph Fourier basis of the agent interaction network, providing a natural and scalable representation. The safety probabilities for these sub-systems are derived as solutions to a set of low-dimensional partial differential equations (PDEs). The proposed decomposition enables existing risk quantification approaches but does so without an exponential increase in computational complexity with respect to the number of agents.
{"title":"Orthogonal Modal Representation in Long-Term Risk Quantification for Dynamic Multi-Agent Systems","authors":"Ryoma Yasunaga;Yorie Nakahira;Yutaka Hori","doi":"10.1109/LCSYS.2024.3522949","DOIUrl":"https://doi.org/10.1109/LCSYS.2024.3522949","url":null,"abstract":"Quantifying long-term risk in large-scale multi-agent systems is critical for ensuring safe operation. However, the high dimensionality of these systems and the rarity of risk events can make the required computations prohibitively expensive. To overcome this challenge, we introduce a graph-based representation and efficient risk quantification techniques tailored for stochastic multi-agent systems. A key technical innovation is a systematic approach to decompose the estimation problem of system-wide safety probabilities into smaller, lower-dimensional sub-systems with sub-safe sets. This decomposition leverages the graph Fourier basis of the agent interaction network, providing a natural and scalable representation. The safety probabilities for these sub-systems are derived as solutions to a set of low-dimensional partial differential equations (PDEs). The proposed decomposition enables existing risk quantification approaches but does so without an exponential increase in computational complexity with respect to the number of agents.","PeriodicalId":37235,"journal":{"name":"IEEE Control Systems Letters","volume":"8 ","pages":"3177-3182"},"PeriodicalIF":2.4,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10816487","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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