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Titlebook: Distributed Event-triggered Control; Scalability and Robu Zhongkui Li,Bin Cheng,Shiqi Zhang Book 2023 The Editor(s) (if applicable) and The

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https://doi.org/10.1057/9780230253209In the previous chapters, fully distributed event-triggered protocols have been presented to achieve consensus for multi-agent systems. In practice, a multi-agent system usually needs to execute some tasks while keeping certain specific geometric patterns, which gives rise to the formation control problem.
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Mathematical Preliminaries,This chapter introduces some mathematical preliminaries that will be utilized in the sequel of this book. Basic notations are first provided, and then some results in the graph theory are presented. Subsequently, certain definitions and fundamental results in the areas of stability and robustness are recalled.
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Distributed Robust Event-Triggered Control with Frequency-Domain Uncertainties,In Chap. ., we have studied the robustness of event-triggered control in the presence of matched nonlinear uncertainties or uncertainties generated by exosystems from the perspectives of nonlinear control such as sliding mode control and output regulation.
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Fully Distributed Consensus Control with Event-Triggered Communication,onsist of event-based control laws and event triggering functions, to ensure that the states of the agents reach agreement. The control laws rely on the local information sampled at discrete event instants and the triggering functions determine these event instants, at which time each agent broadcas
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Fully Distributed Event-Triggered Consensus with Discrete Communication and Control,on of the network or continuous communications among neighboring agents. However, those protocols still suffer from two disadvantages. First, they are only applicable to undirected graphs or leader-follower graphs with undirected subgraphs among followers. How to extend them to the general directed
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Distributed Robust Event-Triggered Control with Matching Uncertainties and Output Regulation,osed protocols relied on agents’ accurate dynamics, which are sometimes not available as a result of the widely existing uncertainties or disturbances. This motivates us to study in this chapter distributed event-triggered control problems of multi-agent systems subject to typical time-domain uncert
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Probabilistic Index Histogram for Robust Object Trackingn often suffers from problems of partial occlusion, background cluttering and other appearance corruptions. In this paper, we propose a probabilistic index histogram to improve the discriminative power of the histogram representation. With this modeling, an input frame is translated into an index ma
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