Found. Trends Syst. Control.最新文献

{"title":"Nonlinear Model Reduction by Moment Matching","authors":"G. Scarciotti, A. Astolfi","doi":"10.1561/2600000012","DOIUrl":"https://doi.org/10.1561/2600000012","url":null,"abstract":"Mathematical models are at the core of modern science and technology. An accurate description of behaviors, systems and processes often requires the use of complex models which are difficult to analyze and control. To facilitate analysis of and design for complex systems, model reduction theory and tools allow determining “simpler” models which preserve some of the features of the underlying complex description. A large variety of techniques, which can be distinguished depending on the features which are preserved in the reduction process, has been proposed to achieve this goal. One such a method is the moment matching approach. This monograph focuses on the problem of model reduction by moment matching for nonlinear systems. The central idea of the method is the preservation, for a prescribed class of inputs and under some technical assumptions, of the steady-state output response of the system to be reduced. We present the moment matching approach from this vantage point, covering the problems of model reduction for nonlinear systems, nonlinear time-delay systems, data-driven model reduction for nonlinear systems and model reduction for “discontinuous” input signals. Throughout the monograph linear systems, with their simple structure and strong properties, are used as a paradigm to facilitate understanding of the theory and provide foundation of the terminology and notation. The text is enriched by several numerical examples, physically motivated examples and with connections to well-established notions and tools, such as the phasor transform. G. Scarciotti and A. Astolfi. Nonlinear Model Reduction by Moment Matching. Foundations and Trends © in Systems and Control, vol. XX, no. XX, pp. 1–187, 2017. DOI: 10.1561/XXXXXXXXXX.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128393434","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}

{"title":"Logical Control of Complex Resource Allocation Systems","authors":"S. Reveliotis","doi":"10.1561/2600000010","DOIUrl":"https://doi.org/10.1561/2600000010","url":null,"abstract":"Abstract This document epitomizes the main points of a plenary presentation under the same title that was given by the author at the 14th Workshop on Discrete Event Systems (WODES 2018).","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126016819","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}

{"title":"Observability of Hybrid Dynamical Systems","authors":"E. D. Santis, M. D. Benedetto","doi":"10.1561/2600000009","DOIUrl":"https://doi.org/10.1561/2600000009","url":null,"abstract":"Hybrid systems, i.e., heterogeneous systems that include discrete and continuous time subsystems, have been used to model applications in automotive such as engine, brake, and stability control, as well as air traffic control and manufacturing plant control. Because of their gen- erality (they include as special cases continuous and discrete systems), deriving rigorous controller synthesis procedures is difficult. The most effective hybrid control algorithms are based on full state feedback. However, in the majority of cases, only partial information about the internal state of the hybrid plant can be measured. Observability and detectability are concepts of fundamental importance that establish the conditions for reconstruction of the state of a system and have been thoroughly investigated in the continuous and discrete domain but not as systematically for hybrid systems. Hybrid systems’ observability involves both the discrete structure and the continuous dynamics of the system. A hybrid system is said to be observable when it is possible to reconstruct the discrete as well as the continuous state of the system from the observed output informa- tion. This paper reviews and places in context how the continuous and the discrete dynamics, as well as their interactions, intervene in the observability property of a quite general class of hybrid systems: linear hybrid systems calledH−systems. Our specific objective is to show how the hybrid characteristics of the system come into play and give rise to particular aspects and properties that do not simply generalize the ones that are well-known for traditional dynamical systems. This paper intends to provide a tutorial approach to hybrid systems observability in its various forms to students in control and its application as well as to practitioners in the field. E. De Santis and M.D. Di Benedetto . Observability of Hybrid Dynamical Systems. Foundations and Trends © in Systems and Control, vol. 3, no. 4, pp. 363–540, 2016. DOI: 10.1561/2600000009.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132442912","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}

{"title":"Sensor Fault Diagnosis","authors":"V. Reppa, M. Polycarpou, C. Panayiotou","doi":"10.1561/2600000007","DOIUrl":"https://doi.org/10.1561/2600000007","url":null,"abstract":"This tutorial investigates the problem of the occurrence of multiple faults in the sensors used to monitor and control a network of cyberphysical systems. The goal is to formulate a general methodology, which will be used for designing sensor fault diagnosis schemes with emphasis on the isolation of multiple sensor faults, and for analyzing the performance of these schemes with respect to the design parameters and system characteristics. The backbone of the proposed methodology is the design of several monitoring and aggregation cyber agents (modules) with specific properties and tasks. The monitoring agents check the healthy operation of sets of sensors and infer the occurrence of faults in these sensor sets based on structured robustness and sensitivity properties. These properties are obtained by deriving analytical redundancy relations of observer-based residuals sensitive to specific subsets of sensor faults, and adaptive thresholds that bound the residuals under healthy conditions, assuming bounded modeling uncertainty and measurement noise. The aggregation agents are employed to collect and process the decisions of the agents, while they apply diagnostic reasoning to isolate combinations of sensor faults that have possibly occurred. The design and performance analysis methodology is presented in the context of three different architectures: for cyber-physical systems that consist of a set of interconnected systems, a distributed architecture and a decentralized architecture, and for cyber-physical systems that are treated as monolithic, a centralized architecture. For all three architectures, the decomposition of the sensor set into subsets of sensors plays a key role in their ability to isolate multiple sensor faults. A discussion of the challenges and benefits of the three architectures is provided, based on the system scale, the type of system nonlinearities, the number of sensors and the communication needs. Lastly, this tutorial concludes with a discussion of open problems in fault diagnosis. V. Reppa, M. M. Polycarpou and C. G. Panayiotou. Sensor Fault Diagnosis. Foundations and Trends © in Systems and Control, vol. 3, no. 1-2, pp. 1–248, 2016. DOI: 10.1561/2600000007. Full text available at: http://dx.doi.org/10.1561/2600000007","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126938268","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}

{"title":"Positive Markov Jump Linear Systems","authors":"P. Bolzern, P. Colaneri","doi":"10.1561/2600000006","DOIUrl":"https://doi.org/10.1561/2600000006","url":null,"abstract":"This paper presents a comprehensive study of continuous-time Positive Markov Jump Linear Systems (PMJLS). A PMJLS can be seen as a dynamical system that switches within a finite set of linear timeinvariant subsystems according to a stochastic switching signal modeled as a Markov chain, and describes the time-evolution of nonnegative variables under nonnegative inputs. Contrary to the well-studied general class of Markov Jump Linear Systems (MJLS), positivity endows the model with peculiar properties. The paper collects some existing results together with original developments on the stability analysis of PMJLS and the study of their input-output properties. In particular, conditions for stability of PMJLS are discussed, mainly based on Linear Programming problems. Similar computational tools are derived to analyze performance measures, such as L1, L2 and L∞ costs and the respective input-output induced gains. The second part of the paper is devoted to the class of Dual switching Positive Markov Jump Linear Systems (D-PMJLS), namely PMJLS affected by an additional switching variable which can be either an unknown disturbance or a control signal available to the designer for stabilization and performance optimization. We discuss several problems, including stability, performance analysis, stabilization via switching control, and optimization. Some application examples are introduced to motivate the interest in PMJLS and D-PMJLS. P. Bolzern and P. Colaneri. Positive Markov Jump Linear Systems. Foundations and Trends © in Systems and Control, vol. 2, no. 3-4, pp. 275–427, 2015. DOI: 10.1561/2600000006. Full text available at: http://dx.doi.org/10.1561/2600000006","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115774580","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}

{"title":"Switched Positive Linear Systems","authors":"F. Blanchini, P. Colaneri, M. E. Valcher","doi":"10.1561/2600000005","DOIUrl":"https://doi.org/10.1561/2600000005","url":null,"abstract":"Positive systems are an important class of systems that frequently arise in application areas, such as in the chemical process industry, electronic circuit design, communication networks, and biology. The study of the stability of such systems differs from standard systems in that the analysis focuses only on the trajectories generated under positivity constraints. Switched positive systems also arise in a variety of applications. Examples can be found in TCP congestion control, in processes described by non-homogeneous Markov chains, in image processing, in biochemical networks, and so on. In comparison to general switched systems, that have received a lot of attention in the past years, the theory for positive switched systems is still in its infancy. Switched Positive Linear Systems studies the stability, performance evaluation, stabilization via switching control, and optimal control of (continuous-time and linear) positive switched systems. It provides a review of the results that have already been established in the literature. Other results, especially those related to norm computation and optimization, are new and are presented integrated with previous ones. Switched Positive Linear Systems provides a comprehensive and timely introduction to the study of such systems. Readers who are new to the topic will find everything required to understand such systems in a concise and accessible form.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"58 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123387016","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}

{"title":"Convergence Rate of Distributed Averaging Dynamics and Optimization in Networks","authors":"A. Nedić","doi":"10.1561/2600000004","DOIUrl":"https://doi.org/10.1561/2600000004","url":null,"abstract":"Recent years have seen the advent of new large cyber-physical systems such as sensor and social networks. These network systems are typically spatially distributed over a large area and may consists of hundreds of agents in smart-sensor networks to millions of agents in social networks. As such, they do not possess a central coordinator or a central point for access to the complete system information. This lack of central entity makes the traditional (centralized) optimization and control techniques inapplicable, thus necessitating the development of new distributed computational models and algorithms to support efficient operations over such networks. This tutorial provides an overview of the convergence rate of distributed algorithms for coordination and its relevance to optimization in a system of autonomous agents embedded in a communication network, where each agent is aware of (and can communicate with) its local neighbors only. The focus is on distributed averaging dynamics for consensus problems and its role in consensus-based gradient methods for convex optimization problems, where the network objective function is separable across the constituent agents. The tutorial will be of interest to researchers and engineers working on a wide-variety of operations research, networking and optimization problems.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129436312","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}

{"title":"Game Theory: Models, Numerical Methods and Applications","authors":"D. Bauso","doi":"10.1561/2600000003","DOIUrl":"https://doi.org/10.1561/2600000003","url":null,"abstract":"Game theory is the theory of strategic thinking. Developed for military purposes and defense, in the past it has also been used as an alternative and complementary approach to deal with robustness in the presence of worst-case uncertainties or disturbances in many areas such as economics, engineering, computer science, just to name a few. However, game theory is recently gaining ground in systems and control engineering, mostly in engineered systems involving humans, where there is a trend to use game theoretic tools to design protocols that will provide incentives for people to cooperate. For instance, scientists tend to use game theoretic tools to design optimal traffic flows, or predicting or avoiding blackouts in power networks or congestion in cyber-physical networked controlled systems. Incentives to cooperate are also crucial in dynamic resource allocation, multi-agent systems and social models (including social and economic networks). This paper assembles the material of two graduate courses given at the Department of Engineering of the University of Oxford in June-July 2013 and at the Department of Electrical and Electronic Engineering of Imperial College, in October-December 2013. The paper covers the foundations of the theory of noncooperative and cooperative games, both static and dynamic. It also highlights new trends in cooperative differential games, learning, approachability (games with vector payoffs) and mean-field games (large number of homogeneous players). The course emphasizes theoretical foundations, mathematical tools, modeling, and equilibrium notions in different environments.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"32 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114032148","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}

{"title":"Port-Hamiltonian Systems Theory: An Introductory Overview","authors":"A. Schaft, D. Jeltsema","doi":"10.1561/2600000002","DOIUrl":"https://doi.org/10.1561/2600000002","url":null,"abstract":"An up-to-date survey of the theory of port-Hamiltonian systems is given, emphasizing novel developments and relationships with other formalisms. Port-Hamiltonian systems theory yields a systematic framework for network modeling of multi-physics systems. Examples from different areas show the range of applicability. While the emphasis is on modeling and analysis, the last part provides a brief introduction to control of port-Hamiltonian systems.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127769526","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}

{"title":"Hybrid Dynamical Systems: An Introduction to Control and Verification","authors":"Hai Lin, P. Antsaklis","doi":"10.1561/2600000001","DOIUrl":"https://doi.org/10.1561/2600000001","url":null,"abstract":"Hybrid dynamical systems are a class of complex systems that involve interacting discrete-eventand continuous-variable dynamics. They are important in applications in embedded systems,cyber-physical systems, robotics, manufacturing systems, traffic management, bio-molecular networks,and have recently been at the center of intense research activity in the control theory,computer-aided verification, and artificial intelligence communities. This paper provides a tutorialintroduction to this multidisciplinary research area. A number of fundamental topics, such asmodeling, abstraction, verification, supervisory control, stability analysis, stabilization, andoptimal control of hybrid systems are introduced and discussed. Additionally, more advanced topicsare briefly discussed at the end of each chapter with references given for further reading.","PeriodicalId":306000,"journal":{"name":"Found. Trends Syst. Control.","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128753232","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}