Titlebook: Machine Behavior Design And Analysis; A Consensus Perspect Yinyan Zhang,Shuai Li Book 2020 Springer Nature Singapore Pte Ltd. 2020 distribu

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記成螞蟻

Discrete-Time Biased Min-Consensus,min-consensus protocol and is convergent in finite time. It should be noted that the protocol here is not obtained by using difference rules to the continuous-time biased min-consensus protocol in the previous chapter, and thus the theoretical analysis is different. The convergence property of the d

invade

Biased Consensus Based Distributed Neural Network,is described as a linear program with the aid of the optimality principle of dynamic programming. Then, continuous-time recurrent neural networks related to consensus protocols are designed for solve the linear program, in which each node in the shortest path problem is represented by a neuron. It i

偏離

FAST

Adaptive Near-Optimal Consensus,re complicated scenario of the problem discussed in the previous chapter. Following the idea in the previous chapter, the problem is described as a dynamic optimization problem, i.e., an optimal control problem, which is reduced into a simpler convex optimization problem via using the Taylor expansi

Harpoon

Near-Optimal Consensus,he closed-loop system is exponentially asymptotically stable, by which the conclusion about the asymptotic optimality of the consensus protocol is also derived. The effectiveness of the scheme is illustrated via numerical simulations.

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