【摘要】：隨著計(jì)算機(jī)、信息、自動(dòng)化等學(xué)科的發(fā)展,多智能系統(tǒng)的協(xié)調(diào)控制在實(shí)際工程中展示出廣闊的應(yīng)用前景。一致性問題是多智能體協(xié)調(diào)控制的基礎(chǔ)問題,現(xiàn)已成為系統(tǒng)與控制科學(xué)領(lǐng)域的研究熱點(diǎn)之一。本文以圖論、矩陣分析和Lyapunov穩(wěn)定性理論為工具,圍繞多智能體系統(tǒng)一致性控制中存在的若干問題展開研究。本文的主要內(nèi)容如下:1.研究了具有通訊時(shí)延的二階非線性多智能體在時(shí)間控制切換拓?fù)湎碌囊恢滦詥栴}。通過引入狀態(tài)變換,得到降階的一致性誤差系統(tǒng),于是多智能體系統(tǒng)的一致性問題轉(zhuǎn)化為誤差系統(tǒng)的穩(wěn)定性問題。最后,構(gòu)造Lyapunov-Krasovskii泛函推導(dǎo)出一致性協(xié)議的設(shè)計(jì)方法并得到拓?fù)淝袚Q信號(hào)的最小平均駐留時(shí)間。2.研究了二階非線性多智能體系統(tǒng)在狀態(tài)控制切換拓?fù)湎碌囊恢滦詥栴}。文中引入狀態(tài)變換,并證明了二階多智能體系統(tǒng)可由一個(gè)一階多智能體系統(tǒng)等價(jià)地分析。首先,在固定拓?fù)淝闆r下,得到一致性協(xié)議的設(shè)計(jì)方法。然后,設(shè)計(jì)狀態(tài)控制的拓?fù)淝袚Q規(guī)則,并構(gòu)造共同Lyapunov函數(shù),證明在所設(shè)計(jì)的一致性協(xié)議和拓?fù)淝袚Q規(guī)則作用下,二階非線性多智能體在切換拓?fù)渎?lián)合包含生成樹的情況下可達(dá)到一致。3.研究了高階非線性多智能體系統(tǒng)在復(fù)雜環(huán)境下的一致性問題。一方面,研究了智能體在執(zhí)行器受到Backlash-like磁滯影響并且控制方向未知情況下的一致性問題。文中利用Backlash-like磁滯的性質(zhì),將磁滯輸出分解為線性輸入和有界擾動(dòng)的疊加。接著,采用新型的Nussbaum函數(shù),解決了多智能體未知控制方向的問題。最后,利用反步法,并結(jié)合神經(jīng)網(wǎng)絡(luò),推導(dǎo)出分布式自適應(yīng)神經(jīng)網(wǎng)絡(luò)一致性協(xié)議。另一方面,研究了具有狀態(tài)時(shí)延的高階非線性多智能體系統(tǒng)一致性問題。基于反步法,利用神經(jīng)網(wǎng)絡(luò)補(bǔ)償不確定非線性項(xiàng),提出自適應(yīng)一致性協(xié)議。同時(shí),通過估計(jì)神經(jīng)網(wǎng)絡(luò)權(quán)重矩陣的上界,減少了自適應(yīng)參數(shù)的數(shù)量,從而降低了計(jì)算負(fù)荷。最終,設(shè)計(jì)Lyapunov-Krasovskii泛函,證明了所提出一致性協(xié)議的有效性。4.研究了異質(zhì)多智能體系統(tǒng)的分組一致性,并考慮通訊拓?fù)渲写嬖诖砀?jìng)爭(zhēng)關(guān)系的負(fù)權(quán)重邊。首先,考慮一類半異質(zhì)的多智能體系統(tǒng),即只允許不同分組中的智能體的動(dòng)力學(xué)模型是異質(zhì)的。利用線性系統(tǒng)的小增益定理,設(shè)計(jì)了分布式狀態(tài)反饋的分組一致性協(xié)議。然后,考慮一類異質(zhì)多智能體系統(tǒng)的分組一致性,這時(shí)所有智能體的動(dòng)力學(xué)模型都允許是不同的,結(jié)合輸出調(diào)節(jié)理論和小增益定理,分別提出基于狀態(tài)反饋和動(dòng)態(tài)輸出反饋兩種分組一致性協(xié)議。最終揭示組內(nèi)耦合關(guān)系和組間耦合關(guān)系對(duì)多智能體系統(tǒng)分組一致性的影響。
[Abstract]:With the development of computer, information, automation and other disciplines, the coordinated control of multi-intelligent system has shown a broad application prospect in practical engineering. The consistency problem is the basic problem of multi-agent coordinated control, and has become one of the hotspots in the field of system and control science. Using graph theory, matrix analysis and Lyapunov stability theory as tools, this paper focuses on several problems in consistency control of multi-agent systems. The main contents of this paper are as follows: 1. The consistency problem of a second order nonlinear multi-agent with communication delay under time-controlled switching topology is studied. By introducing the state transformation, a reduced order consistency error system is obtained, so the consistency problem of the multi-agent system is transformed into the stability problem of the error system. Finally, the Lyapunov-Krasovskii functional is constructed to derive the design method of the consistency protocol and the minimum mean dwell time of the topology switching signal is obtained. 2. 2. In this paper, the consistency problem of second order nonlinear multi-agent systems under state control switching topology is studied. In this paper, the state transformation is introduced, and it is proved that the second-order multi-agent system can be analyzed equally by a first-order multi-agent system. Firstly, in the case of fixed topology, the design method of conformance protocol is obtained. Then, the topology switching rules of state control are designed, and the common Lyapunov function is constructed. The second order nonlinear multi-agent is consistent in the case of switching topology joint inclusion spanning tree. 3. 3. The consistency problem of high order nonlinear multi-agent systems in complex environments is studied. On the one hand, the consistency problem of the agent is studied when the actuator is affected by the Backlash-like hysteresis and the control direction is unknown. By using the properties of Backlash-like hysteresis, the hysteresis output is decomposed into the superposition of linear input and bounded disturbance. Then, the new Nussbaum function is used to solve the problem of unknown control direction of multi-agent. Finally, a distributed adaptive neural network consistency protocol is derived by using the backstepping method and the neural network. On the other hand, the consistency problem of high order nonlinear multi-agent systems with state delay is studied. Based on the backstepping method, an adaptive consistency protocol is proposed by using neural networks to compensate for uncertain nonlinear terms. At the same time, by estimating the upper bound of the neural network weight matrix, the number of adaptive parameters is reduced and the computational load is reduced. Finally, the Lyapunov-Krasovskii functional is designed to prove the effectiveness of the proposed conformance protocol. 4. 4. The packet consistency of heterogeneous multi-agent systems is studied, and the negative weight edges representing competition in communication topology are considered. Firstly, we consider a class of semi-heterogeneous multi-agent systems, that is, the dynamic model of agents in different groups is heterogeneous. Based on the small gain theorem of linear systems, a distributed state feedback packet consistency protocol is designed. Then, considering the grouping consistency of a class of heterogeneous multi-agent systems, the dynamic models of all agents are allowed to be different, combined with the output regulation theory and the small gain theorem. Two packet consistency protocols based on state feedback and dynamic output feedback are proposed respectively. Finally, the effects of intra-group coupling and inter-group coupling on packet consistency in multi-agent systems are revealed.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP18;TP13

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