The Experts below are selected from a list of 755862 Experts worldwide ranked by ideXlab platform
Zhiyong Chen - One of the best experts on this subject based on the ideXlab platform.
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A General Framework for tackling the output regulation problem
IEEE Transactions on Automatic Control, 2004Co-Authors: Jie Huang, Zhiyong ChenAbstract:Output regulation aims to achieve, in addition to closed-loop stability, asymptotic tracking and disturbance rejection for a class of reference inputs and disturbances. Thus, it poses a more challenging problem than stabilization. For over a decade, the nonlinear output regulation problem has been one of the focuses in nonlinear control research, and active research on this problem has generated many fruitful results. Nevertheless, there are two hurdles that impede the further progress of the research on the output regulation problem. The first one is the assumption that the solution or the partial solution of the regulator equations is polynomial. The second one is the lack of a systematic mechanism to handle the global robust output regulation problem. We establish a General Framework that systematically converts the robust output regulation problem for a General nonlinear system into a robust stabilization problem for an appropriately augmented system. This General Framework, on one hand, relaxes the polynomial assumption, and on the other hand, offers a greater flexibility to incorporate recent new stabilization techniques, thus setting a stage for systematically tackling the robust output regulation with global stability.
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A General Framework for output regulation problem
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 1Co-Authors: Jie Huang, Zhiyong ChenAbstract:The paper aims to establish a General Framework that will convert the robust output regulation problem for nonlinear systems into a robust stabilization problem. This new Framework will offer greater flexibility to incorporate new stabilization techniques, thus setting a stage for systematically tackling robust output regulation with global stability.
Jie Huang - One of the best experts on this subject based on the ideXlab platform.
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A General Framework for tackling the output regulation problem
IEEE Transactions on Automatic Control, 2004Co-Authors: Jie Huang, Zhiyong ChenAbstract:Output regulation aims to achieve, in addition to closed-loop stability, asymptotic tracking and disturbance rejection for a class of reference inputs and disturbances. Thus, it poses a more challenging problem than stabilization. For over a decade, the nonlinear output regulation problem has been one of the focuses in nonlinear control research, and active research on this problem has generated many fruitful results. Nevertheless, there are two hurdles that impede the further progress of the research on the output regulation problem. The first one is the assumption that the solution or the partial solution of the regulator equations is polynomial. The second one is the lack of a systematic mechanism to handle the global robust output regulation problem. We establish a General Framework that systematically converts the robust output regulation problem for a General nonlinear system into a robust stabilization problem for an appropriately augmented system. This General Framework, on one hand, relaxes the polynomial assumption, and on the other hand, offers a greater flexibility to incorporate recent new stabilization techniques, thus setting a stage for systematically tackling the robust output regulation with global stability.
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A General Framework for output regulation problem
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 1Co-Authors: Jie Huang, Zhiyong ChenAbstract:The paper aims to establish a General Framework that will convert the robust output regulation problem for nonlinear systems into a robust stabilization problem. This new Framework will offer greater flexibility to incorporate new stabilization techniques, thus setting a stage for systematically tackling robust output regulation with global stability.
Barbara König - One of the best experts on this subject based on the ideXlab platform.
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A General Framework for types in graph rewriting
Acta Informatica, 2005Co-Authors: Barbara KönigAbstract:We investigate a General Framework which can be instantiated in order to obtain type systems for graph rewriting, allowing us to statically infer behavioural properties of a graph. We describe conditions such as the subject reduction property and compositionality that should be satisfied by such a Framework. We present a methodology for proving these conditions, specifically we prove that it is sufficient to show properties that are local to graph transformation rules. In order to show the applicability of this Framework, we describe in several case studies how to integrate existing type systems (for the ?-calculus and the ?-calculus) and a system for typing acyclic graphs.
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FSTTCS - A General Framework for Types in Graph Rewriting
FST TCS 2000: Foundations of Software Technology and Theoretical Computer Science, 2000Co-Authors: Barbara KönigAbstract:A General Framework for typing graph rewriting systems is presented: the idea is to statically derive a type graph from a given graph. In contrast to the original graph, the type graph is invariant under reduction, but still contains meaningful behaviour information. We present conditions, a type system for graph rewriting should satisfy, and a methodology for proving these conditions. In two case studies it is shown how to incorporate existing type systems (for the polyadic π-calculus and for a concurrent object-oriented calculus) into the General Framework.
Tamir Tassa - One of the best experts on this subject based on the ideXlab platform.
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Vector assignment problems: a General Framework
Journal of Algorithms, 2003Co-Authors: Leah Epstein, Tamir TassaAbstract:We present a General Framework for vector assignment problems. In such problems one aims at assigning n input vectors to m machines such that the value of a given target function is minimized. While previous approaches concentrated on simple target functions such as max-max, the General approach presented here enables us to design a polynomial time approximation scheme (PTAS) for a wide class of target functions. In particular, thanks to a novel technique of preprocessing the input vectors, we are able to deal with nonmonotone target functions. Such target functions arise in vector assignment problems in the context of video transmission and broadcasting.
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ESA - Vector Assignment Problems: A General Framework
Algorithms — ESA 2002, 2002Co-Authors: Leah Epstein, Tamir TassaAbstract:We present a General Framework for vector assignment problems. In such problems one aims at assigning n input vectors to m machines such that the value of a given target function is minimized. While previous approaches concentrated on simple target functions such as max-max, the General approach presented here enables us to design a PTAS for a wide class of target functions. In particular we are able to deal with non-monotone target functions and asymmetric settings where the cost functions per machine may be different for different machines. This is done by combining a graph-based technique and a new technique of preprocessing the input vectors.
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Vector assignment problems: A General Framework
Lecture Notes in Computer Science, 2002Co-Authors: Leah Epstein, Tamir TassaAbstract:We present a General Framework for vector assignment problems. In such problems one aims at assigning n input vectors to m machines such that the value of a given target function is minimized. While previous approaches concentrated on simple target functions such as max-max, the General approach presented here enables us to design a PTAS for a wide class of target functions. In particular we are able to deal with non-monotone target functions and asymmetric settings where the cost functions per machine may be different for different machines. This is done by combining a graph-based technique and a new technique of preprocessing the input vectors.
Shell Ying Huang - One of the best experts on this subject based on the ideXlab platform.
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A General Framework for parallel BDI agents in dynamic environments
Web Intelligence and Agent Systems: An International Journal, 2008Co-Authors: Huiliang Zhang, Shell Ying HuangAbstract:In this paper, a General Framework for the parallel BDI model suitable for dynamic environments is proposed. It is a parallel agent architecture that supports the following agent abilities at architecture level: (1) the ability to monitor the environment at all times and respond to emergencies timely; (2) the ability to reconsider and re-schedule goals, intentions and actions in reaction to unexpected or new information; (3) the ability to perform multiple actions at once; (4) the ability to perceive, deliberate and act simultaneously; (5) the ability to prioritize the deliberations and intention executions. We define the functions and the operations of the processing units in the agent and how these units interact, cooperate and synchronize with each other. With the advances in semiconductor technology which allow multiple processing units to be implemented on the same silicon chip, a parallel BDI agent will be an effective way to enable it to perform in a dynamically changing environment when the arrival rate of events is high. We illustrate the working of a parallel agent under the General Framework with an agent simulating the behaviour of a vessel captain navigating in sea. Then the performance of a parallel agent is evaluated against several versions of sequential agents. The issue of how much parallelism and how to configure a parallel agent based on the General Framework are studied by experiments with different configurations of the parallel agent.
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IAT - A General Framework for Parallel BDI Agents
2006 IEEE WIC ACM International Conference on Intelligent Agent Technology, 2006Co-Authors: Huiliang Zhang, Shell Ying HuangAbstract:The traditional BDI agent has 3 basic computational components that generate beliefs, generate intentions and execute intentions. They run in a sequential and cyclic manner. This may introduce several problems. Among them, the inability to watch the environment continuously in dynamic environments may be disastrous. There is also no support for goal and intention reconsideration and consideration of relationships between goals at the architecture level. A parallel BDI agent architecture was proposed in [15] and evaluated in [16]. Based on the work in [15] and [16], we propose in this paper, a General Framework for the parallel BDI agent model. Under this General Framework, parallel BDI agents with different configurations depending on the availability of physical resources may be built. These agents have a number of advantages over the sequential one: 1. changes in the agent's environment can be detected immediately; 2. emergencies will be dealt with immediately; 3. the support is provided at the architecture level for reconsideration of desires/intentions and the consideration of goal relationships when a new belief/desire is generated. We show some example parallel BDI agents with different configurations under the Framework and their performance in a set of experiments.
