發(fā)布時(shí)間：2018-03-06 02:31

  本文選題：平均一致　切入點(diǎn)：收斂速度　出處：《重慶大學(xué)》2014年博士論文　論文類(lèi)型：學(xué)位論文

【摘要】：分布式平均算法已經(jīng)受到極大的關(guān)注，由于在分布式網(wǎng)絡(luò)系統(tǒng)中節(jié)點(diǎn)保持簡(jiǎn)單的狀態(tài)信息并且只與一跳鄰居交換信息.因此，不需要建立或保持復(fù)雜的路由結(jié)構(gòu).而且，網(wǎng)絡(luò)不會(huì)存在由計(jì)算可能被對(duì)手損壞、丟失或者干擾引起的瓶頸鏈接(樹(shù)狀或環(huán)狀結(jié)構(gòu)).最重要的是，平均一致性算法最優(yōu)異的性質(zhì)在于算法最終計(jì)算的值均可以應(yīng)用于整個(gè)網(wǎng)絡(luò)，使網(wǎng)絡(luò)用戶詢問(wèn)任何節(jié)點(diǎn)都能立即得到一個(gè)響應(yīng)，而不是詢問(wèn)或者等待融合中心的反應(yīng).此外，最終計(jì)算的值就是網(wǎng)絡(luò)節(jié)點(diǎn)初始測(cè)量的平均值，由于其在無(wú)線傳感器網(wǎng)絡(luò)中的廣泛應(yīng)用而受到關(guān)注.本論文主要致力于分析分布式通信網(wǎng)絡(luò)的平均一致估計(jì)和優(yōu)化問(wèn)題，其主要內(nèi)容和創(chuàng)新之處可概述如下： ①基于廣播的隨機(jī)多Gossip對(duì)算法的平均一致估計(jì)問(wèn)題 基于無(wú)線傳感器網(wǎng)絡(luò)、點(diǎn)對(duì)點(diǎn)網(wǎng)絡(luò)和ad hoc網(wǎng)絡(luò)的應(yīng)用和普及，我們提出了一個(gè)基于廣播的隨機(jī)多Gossip對(duì)算法，算法適用于任意形式連通的網(wǎng)絡(luò)進(jìn)行信息交換和計(jì)算.不像傳統(tǒng)的隨機(jī)Gossip算法，本章提出的算法是基于push-sum機(jī)制的，使得算法在任意時(shí)鐘周期內(nèi)都能保存和以及權(quán)值，并且允許隨機(jī)擴(kuò)散矩陣不是雙隨機(jī)的.基于弱遍歷理論和信息傳播理論，推導(dǎo)出權(quán)值存在下界，并給出了下界的一個(gè)估計(jì)值.通過(guò)引入一個(gè)誤差勢(shì)函數(shù)，推導(dǎo)出算法以概率1收斂到節(jié)點(diǎn)初始狀態(tài)的平均.此外，本章也提供了擴(kuò)散速度、-收斂時(shí)間以及廣播傳輸次數(shù)的上界.最后，通過(guò)一個(gè)仿真的例子，示例了本章的算法與它相似算法相比較所表現(xiàn)出的優(yōu)勢(shì). ②基于預(yù)測(cè)機(jī)制多智能體網(wǎng)絡(luò)加速平均一致問(wèn)題 探討了多智能體網(wǎng)絡(luò)達(dá)到分布式加權(quán)平均一致的雙積分器的一致加速問(wèn)題.首先，給出了有向和無(wú)向網(wǎng)絡(luò)收斂到加權(quán)平均一致的充要條件，但是收斂速度很慢.為了提升收斂速度，提出一個(gè)預(yù)測(cè)方法加速達(dá)到一致，即利用線性預(yù)測(cè)器通過(guò)當(dāng)前時(shí)刻和過(guò)去時(shí)刻節(jié)點(diǎn)的狀態(tài)來(lái)預(yù)測(cè)將來(lái)節(jié)點(diǎn)的狀態(tài).因此，基于預(yù)測(cè)機(jī)制的一致性協(xié)議就變成了原始一致性協(xié)議和線性預(yù)測(cè)器的凸加權(quán)和的形式，由于忽略冗余狀態(tài)，這使得達(dá)到加權(quán)平均一致的收斂速度變快.而且，對(duì)于無(wú)向網(wǎng)絡(luò)，還給出了混合參數(shù)的可行域以及最優(yōu)值.值得指出的是，加速框架已經(jīng)盡可能地挖掘存儲(chǔ)在內(nèi)存中的當(dāng)前時(shí)刻和過(guò)去時(shí)刻節(jié)點(diǎn)的狀態(tài)的最大潛能，用以提升收斂速度而不增加存儲(chǔ)和計(jì)算負(fù)擔(dān).最后，給出一個(gè)仿真實(shí)驗(yàn)證明方法的有效性. ③單積分器的多智能體網(wǎng)絡(luò)的加權(quán)平均預(yù)測(cè)問(wèn)題 討論了在多智能體網(wǎng)絡(luò)達(dá)到加權(quán)平均一致的前提下，如何同時(shí)提升網(wǎng)絡(luò)的魯棒性以及收斂速度.為了達(dá)到這個(gè)目的，提出了一個(gè)加權(quán)平均預(yù)測(cè)方法，那么網(wǎng)絡(luò)一致性協(xié)議就變?yōu)橐粋�(gè)時(shí)滯的中立型協(xié)議.通過(guò)運(yùn)用Hopf分岔分析技術(shù)，獲得了一個(gè)使網(wǎng)絡(luò)能達(dá)到加權(quán)平均一致所允許的最大通信時(shí)滯.而且，通過(guò)理論分析并與原一致性協(xié)議相比，所得到的結(jié)果不僅增強(qiáng)了網(wǎng)絡(luò)對(duì)于通信時(shí)滯的魯棒性而且提升了網(wǎng)絡(luò)協(xié)議的收斂速度.最后，給出兩個(gè)仿真實(shí)驗(yàn)證明方法的有效性. ④基于時(shí)滯次梯度信息的分布式協(xié)同優(yōu)化 討論了帶有通信時(shí)滯的可計(jì)算的多智能體網(wǎng)絡(luò)的分布式協(xié)同優(yōu)化問(wèn)題，其中，每個(gè)智能體有自己的凸代價(jià)函數(shù)，，并且協(xié)同最小化整個(gè)網(wǎng)絡(luò)的全局代價(jià)函數(shù).為了解決這個(gè)問(wèn)題，提出了一個(gè)基于對(duì)偶平均更新和時(shí)滯次梯度信息的算法，通過(guò)利用Brgman距離函數(shù)分析了衰減步長(zhǎng)情況下算法的收斂性質(zhì).而且，本章提供了收斂速率的一個(gè)緊致上界，它是網(wǎng)絡(luò)規(guī)模和拓?fù)?表現(xiàn)為逆譜距)的一個(gè)函數(shù).最后，給出了一個(gè)仿真實(shí)驗(yàn)證明了本章的算法與其它相似算法相比表現(xiàn)出的優(yōu)勢(shì).
[Abstract]:Distributed average algorithm has received great attention due to the distributed network nodes in the system to maintain state information is simple and only exchange information with one hop neighbors. Therefore, don't need to establish or maintain routing with complicated structure. Moreover, the network does not exist by calculating the opponent may be lost or damaged, the interference caused by the bottleneck link (or tree ring structure). The most important is the average consensus algorithm is the most excellent properties of final algorithm can be applied to the calculation of the value of the whole network, the network users ask any node can immediately get a response, rather than asking or waiting for the fusion center reaction. In addition, the final calculation value is the initial network node the measured average value, because of its wide application in wireless sensor networks and the average attention. This dissertation focuses on a distributed communication network The main content and innovation of unanimous estimation and optimization can be summarized as follows:
Average uniform estimation of random multiple Gossip pairs based on broadcast
Based on wireless sensor network, peer-to-peer applications and network ad hoc and popularization of the network, we propose a multi Gossip based on random broadcast algorithm, algorithm for communicating with any form of network information exchange and random calculation. Unlike the traditional Gossip algorithm, the proposed algorithm is based on the push-sum mechanism. The algorithm at any clock cycle can be saved and weights, and allows the random diffusion matrix is not double random. Weak ergodic theory and based on the theory of information communication, the weights of existing lower bounds are derived, and gives a lower bound value. By introducing an error function and derive the algorithm convergence by probability 1 the average node initial state. In addition, this chapter also provides the diffusion speed of - convergence time and the upper bound of broadcasting transmission times. Finally, through a simulation example, the example of this chapter is The superiority of the method is compared with its similar algorithm.
Acceleration average consistency problem of multi agent network based on prediction mechanism
Accelerate the consistent multi-agent networks of double integrator distributed weighted average consensus problem. First of all, gives the sufficient and necessary conditions of undirected and weighted network to converge to the average of the same, but the convergence speed is very slow. In order to improve the convergence speed, put forward a prediction method to speed up, namely the use of linear predictor to predict the future status of nodes through the current time and past time node state. Therefore, the consistency protocol based on prediction mechanism becomes the original agreement and convex weighted linear predictor and form, by ignoring the redundant state, which makes the weighted average convergence rate is reached consistent faster. Moreover, for free to network, gives the feasible domain of mixing parameters and the optimal value. It is worth noting that the framework has been accelerated as much as possible mining is stored in the memory of the current and past The maximum potential of nodes at any time is used to improve the convergence speed without increasing the burden of storage and computation. Finally, a simulation experiment is given to demonstrate the effectiveness of the method.
The weighted average prediction problem of the multi agent network of a single integrator
The premise of the weighted average consensus in multi-agent networks, how to enhance the network robustness and convergence speed. In order to achieve this goal, proposes a weighted average forecasting method, then the network consistency protocol is a protocol neutral delay. By using Hopf bifurcation analysis technology, obtain a network can reach the maximum allowable uniform weighted average communication delay. Moreover, through theoretical analysis and compared with the original agreement, the result not only enhances the network robustness to the communication delay and enhance the convergence speed of the network protocol. Finally, gives two effective methods to prove the simulation experiment.
Distributed cooperative optimization based on time-delay subgradient information
This paper discusses the distributed computational multi-agent networks with communication delays of the collaborative optimization problem, where each agent has its own convex cost function, and the collaborative global cost function minimization of the whole network. In order to solve this problem, proposed a based on the average delay time and even update the gradient information through the algorithm. Using the Brgman distance function to analyze the convergence properties of the algorithm step attenuation situation. Moreover, this chapter provides a tight upper bound of convergence rate, it is the network size and topology (expressed as the inverse spectral distance) a function. Finally, a simulation experiment is given to prove the algorithm showed in this chapter compared with other similar algorithms.

【學(xué)位授予單位】：重慶大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN92

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 溫顯斌;;無(wú)線傳感器網(wǎng)絡(luò)中分布式信息融合研究進(jìn)展[J];天津理工大學(xué)學(xué)報(bào);2013年02期

相關(guān)博士學(xué)位論文 前1條

1 朱善迎;基于協(xié)同策略的工業(yè)無(wú)線網(wǎng)絡(luò)分布式估計(jì)問(wèn)題研究[D];上海交通大學(xué);2013年

本文編號(hào)：1572971