本文選題：非線性系統(tǒng) + 隨機系統(tǒng)�。� 參考：《南京理工大學》2016年博士論文

【摘要】：在現(xiàn)實世界中,大部分控制系統(tǒng)具有本質(zhì)非線性、不確定性,而且通常受到輸入約束等因素的影響.因此,具有輸入約束的不確定非線性系統(tǒng)的研究引起了廣泛的關注.但此類系統(tǒng)尚且沒有統(tǒng)一的理論與方法,必須針對不同類型的輸入約束和控制問題分別進行分析與處理.本文在已有工作的基礎上,基于神經(jīng)網(wǎng)絡逼近理論,研究了具有輸入約束的兩類控制問題:一類是隨機非線性系統(tǒng)的自適應控制;一類是非線性多智能體系統(tǒng)的分布式協(xié)調(diào)控制.主要研究工作如下:1.針對具有不同類型輸入約束的不確定隨機非線性時滯系統(tǒng),研究了自適應神經(jīng)網(wǎng)絡有界鎮(zhèn)定問題.首先,對于飽和輸入,給出了單輸入單輸出的隨機非線性時滯系統(tǒng)的自適應神經(jīng)網(wǎng)絡控制方案.其次,對于死區(qū)輸入,設計了隨機非線性時滯互聯(lián)大系統(tǒng)自適應神經(jīng)網(wǎng)絡分散控制器.所提出的控制方案均保證了閉環(huán)系統(tǒng)的所有信號是依概率有界的.仿真算例表明了設計方案的可行性.2.針對帶有輸入約束的不確定切換隨機非線性系統(tǒng),研究了自適應神經(jīng)網(wǎng)絡跟蹤控制問題.首先,考慮具有飽和輸入的嚴格反饋切換隨機非線性系統(tǒng).結合神經(jīng)網(wǎng)絡逼近理論、反步遞推設計方法和公共李雅普諾夫函數(shù)方法,給出了自適應神經(jīng)網(wǎng)絡跟蹤控制方案.所提出的控制方案保證了閉環(huán)系統(tǒng)的所有信號是依概率有界的,而且跟蹤誤差可以收斂到原點的充分小鄰域內(nèi).其次,考慮具有滯回特性的純反饋切換隨機非線性系統(tǒng).利用均值定理將系統(tǒng)的非仿射函數(shù)轉化為仿射形式,進而提出了基于神經(jīng)網(wǎng)絡逼近的自適應跟蹤控制方案.數(shù)值算例說明了設計方法的有效性.3.針對具有飽和輸入的非線性多智能體系統(tǒng),研究了分布式一致性控制問題.首先,應用神經(jīng)網(wǎng)絡逼近未知非線性函數(shù),引入輔助系統(tǒng)補償飽和輸入的影響并結合命令濾波技術和反步遞推設計方法,獲得了分布式一致性控制方案.然后利用李雅普諾夫穩(wěn)定性理論,證明了閉環(huán)系統(tǒng)的所有信號是半全局一致最終有界的,而且一致性誤差收斂到原點的小鄰域內(nèi).在此基礎上,進一步研究了一類帶有執(zhí)行器故障的非線性多智能體系統(tǒng)的分布式包含控制問題,提出了分布式包含控制器的有效設計方法.仿真結果表明了所提出控制方法的有效性.4.針對帶有未知死區(qū)輸入的非仿射非線性多智能體系統(tǒng),研究了指定性能分布式一致性控制問題.首先應用神經(jīng)網(wǎng)絡逼近未知非線性函數(shù)并利用指定性能函數(shù)實現(xiàn)同步誤差的穩(wěn)態(tài)和暫態(tài)性能,然后結合李雅普諾夫穩(wěn)定性理論和動態(tài)面控制技術,給出了不依賴于死區(qū)參數(shù)的分布式一致性控制方案.所提出的控制方案保證了閉環(huán)系統(tǒng)的所有信號是半全局一致最終有界的,而且跟隨者的輸出以預定義的誤差同步于領導者信號.數(shù)值算例說明了控制方案的可行性.
[Abstract]:In the real world, most of the control systems have essential nonlinearity, uncertainty, and are usually influenced by factors such as input constraints. Therefore, the study of uncertain nonlinear systems with input constraints has aroused widespread concern. However, there is no unified theory and method for such systems, which must be based on different types of input. On the basis of the existing work, based on the neural network approximation theory, this paper studies two kinds of control problems with input constraints: one is the adaptive control of stochastic nonlinear systems and the other is the distributed coordinated control of nonlinear multi-agent systems. The main research work is as follows: 1. For uncertain stochastic nonlinear time-delay systems with different types of input constraints, an adaptive neural network bounded stabilization problem is studied. Firstly, for saturated input, an adaptive neural network control scheme for stochastic nonlinear time-delay systems with single input and single output is given. The proposed control scheme guarantees that all the signals of the closed loop system are bounded by probability. The simulation example shows the feasibility of the design scheme.2. for an uncertain switched stochastic nonlinear system with input constraints, and the adaptive neural network tracking control question is studied. First, a strict feedback switched stochastic nonlinear system with saturated input is considered. Combining the neural network approximation theory, the backstepping design method and the common Lyapunov function method, the adaptive neural network tracking control scheme is given. The proposed control scheme guarantees that all the signals of the closed loop system are bounded by probability. And the tracking error can be converged to the sufficient small neighborhood of the origin. Secondly, a pure feedback switched stochastic nonlinear system with hysteresis characteristics is considered. By means of the mean theorem, the non affine function of the system is transformed into an affine form, and a self-adaptive tracking control scheme based on neural network approximation is proposed. The effectiveness of the method.3. studies the distributed consistency control problem for the nonlinear multi-agent systems with saturated input. First, the neural network is applied to the unknown nonlinear function, the auxiliary system is introduced to compensate the influence of the saturated input, and the distributed consistency is obtained by combining the command filtering technique and the backstepping design method. By using Lyapunov stability theory, it is proved that all the signals in the closed loop system are semi global and final bounded, and the consistency error converges to the small neighborhood of the origin. On this basis, the distributed inclusion control problem of a class of non linear multi-agent systems with actuator failures is further studied. An effective design method of distributed inclusion controller is proposed. The simulation results show that the effectiveness of the proposed control method.4. is used to study the distributed conformance control problem of the designated performance for non affine nonlinear multi-agent systems with unknown dead zone input. The qualitative function realizes the steady-state and transient performance of the synchronization error. Then, combining the Lyapunov stability theory and the dynamic surface control technology, the distributed conformance control scheme is given without the dead zone parameters. The proposed control scheme guarantees that all the signal numbers of the closed loop system are semi global and final bounded, and the following are followed by the control scheme. The output is synchronized to the leader signal with predefined error. Numerical examples illustrate the feasibility of the control scheme.
【學位授予單位】：南京理工大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：TP13;TP183

【參考文獻】

相關期刊論文 前2條

1 ;Direct adaptive neural control for stabilization of nonlinear time-delay systems[J];Science China(Information Sciences);2010年04期

2 李靖;李俊民;陳為勝;;隨機非線性嚴格反饋系統(tǒng)的自適應神經(jīng)網(wǎng)絡輸出反饋鎮(zhèn)定[J];自動化學報;2010年03期

相關博士學位論文 前5條

1 王芳;具有輸入輸出約束特性的非線性系統(tǒng)自適應模糊控制[D];廣東工業(yè)大學;2015年

2 彭鈞敏;非線性網(wǎng)絡系統(tǒng)協(xié)調(diào)控制[D];浙江大學;2014年

3 李永明;非匹配不確定非線性系統(tǒng)自適應模糊控制[D];大連海事大學;2014年

4 周琪;幾類不確定非線性系統(tǒng)的智能控制問題研究[D];南京理工大學;2013年

5 王煥清;幾類隨機非線性系統(tǒng)的自適應神經(jīng)網(wǎng)絡控制[D];青島大學;2013年

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本文編號：1983096