本文選題：隨機時滯　切入點：丟包　出處：《黑龍江大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著網(wǎng)絡(luò)技術(shù)、通信技術(shù)和自動控制技術(shù)的融合與發(fā)展,網(wǎng)絡(luò)化控制系統(tǒng)已成為人們關(guān)注的焦點。網(wǎng)絡(luò)控制系統(tǒng)因具有成本低、易資源共享和遠程操作等優(yōu)點,而被廣泛用于國民經(jīng)濟建設(shè)中。但隨著網(wǎng)絡(luò)系統(tǒng)規(guī)模的增大,復(fù)雜程度的增加,因網(wǎng)絡(luò)承載能力和通信帶寬的有限性使得網(wǎng)絡(luò)數(shù)據(jù)交換往往存在隨機滯后和丟包現(xiàn)象。此外,環(huán)境干擾以及傳感器自身損耗也會使系統(tǒng)具有不確定性。針對上述問題,本文應(yīng)用射影理論和線性最小方差意義下的分布式融合算法,研究具有多隨機時滯和丟包網(wǎng)絡(luò)化隨機不確定系統(tǒng)的融合濾波問題,主要研究內(nèi)容如下:對數(shù)據(jù)包帶有和不帶有時間戳的隨機滯后和丟包的多傳感器離散線性隨機系統(tǒng),分別推導(dǎo)了依賴隨機變量值和依賴隨機變量概率的任兩個傳感器子系統(tǒng)之間的濾波誤差互協(xié)方差陣�；谝延械木植繛V波器和所推得的濾波誤差互協(xié)方差陣,分別設(shè)計了依賴隨機變量值和依賴隨機變量概率的分布式和集中式融合濾波器,進一步,對依賴隨機變量概率的分布式和集中式融合濾波器,分析了穩(wěn)態(tài)特性,并給出了穩(wěn)態(tài)融合濾波器存在的一個充分條件。對帶有隨機乘性噪聲和多步隨機滯后多丟包的多傳感器離散線性隨機系統(tǒng),提出了局部子系統(tǒng)的線性最小方差最優(yōu)線性濾波器。當(dāng)狀態(tài)方程和觀測方程中均含有乘性噪聲時,推導(dǎo)了任兩個傳感器子系統(tǒng)間的濾波誤差互協(xié)方差陣,提出了分布式按矩陣加權(quán)融合濾波器和集中式融合濾波器,并給出了穩(wěn)態(tài)融合濾波器存在的一個充分條件。進一步,當(dāng)僅狀態(tài)方程含有乘性噪聲時,為了減小計算負擔(dān),又提出了避免計算互協(xié)方差陣的協(xié)方差交叉融合濾波器。對帶有不確定觀測、多隨機滯后和丟包的多傳感器線性離散隨機系統(tǒng),設(shè)計了線性最小方差意義下的局部最優(yōu)線性濾波器,推導(dǎo)了任兩個傳感器子系統(tǒng)間的誤差互協(xié)方差陣,給出了按矩陣加權(quán)分布式融合濾波器。對系統(tǒng)僅含有一步隨機滯后情況,推導(dǎo)了集中式融合濾波器,并給出了穩(wěn)態(tài)存在的一個充分條件。
[Abstract]:With the integration and development of network technology, communication technology and automatic control technology, networked control system has become the focus of attention. Network control system has the advantages of low cost, easy resource sharing and remote operation. But with the increase of the scale of network system and the increase of complexity, the network data exchange often has the phenomenon of random delay and packet loss due to the limitation of network carrying capacity and communication bandwidth. Environmental interference and sensor loss also make the system uncertain. In view of the above problems, this paper applies projective theory and distributed fusion algorithm in the sense of linear minimum variance. In this paper, the problem of fusion filtering for networked stochastic uncertain systems with multiple stochastic delays and packet loss is studied. The main contents are as follows: for multisensor discrete linear stochastic systems with and without timestamp, stochastic delay and packet loss are studied. The filtering error mutual covariance matrix between any two sensor subsystems depending on random variable value and probability of random variable is derived, respectively. Based on the existing local filter and the derived filtering error cross covariance matrix, Distributed and centralized fusion filters depending on the probability of random variables and random variables are designed, respectively. Furthermore, the steady-state characteristics of distributed and centralized fusion filters dependent on probability of random variables are analyzed. A sufficient condition for the existence of a steady-state fusion filter is given. For a multisensor discrete linear stochastic system with stochastic multiplicative noise and multi-step stochastic delay and multiple packet loss, A linear minimum variance optimal linear filter for local subsystems is proposed. When multiplicative noise is present in both the state equation and the observation equation, the filtering error covariance matrix between any two sensor subsystems is derived. A distributed matrix weighted fusion filter and a centralized fusion filter are proposed, and a sufficient condition for the existence of the steady-state fusion filter is given. Furthermore, when only the equation of state contains multiplicative noise, in order to reduce the computational burden, A covariance crossover fusion filter is proposed to avoid computing the cross covariance matrix. For multisensor linear discrete stochastic systems with uncertain observations, multiple stochastic delays and packet loss, the covariance cross fusion filter is proposed. A local optimal linear filter is designed in the sense of linear minimum variance. The error mutual covariance matrix between any two sensor subsystems is derived, and the distributed fusion filter weighted by matrix is given. A centralized fusion filter is derived and a sufficient condition for the existence of steady state is given.
【學(xué)位授予單位】：黑龍江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TP202;TN713

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