本文選題：非線性系統(tǒng) + 輸入飽和　； 參考：《江南大學(xué)》2017年碩士論文

【摘要】：在實(shí)際的工業(yè)生產(chǎn)中,系統(tǒng)不能傳輸無限大的控制信號(hào),所以飽和現(xiàn)象廣泛存在于各種系統(tǒng)中,然而人們?cè)谠O(shè)計(jì)控制器時(shí)往往會(huì)忽略系統(tǒng)的飽和現(xiàn)象,當(dāng)系統(tǒng)發(fā)生飽和時(shí),系統(tǒng)性能顯著下降。飽和現(xiàn)象曾引起了許多悲劇,這些悲劇讓人們開始意識(shí)到飽和的存在及其重要影響。經(jīng)過國內(nèi)外學(xué)者長時(shí)間的探索,飽和約束控制取得了巨大的發(fā)展。過去提出的控制方法大多基于線性系統(tǒng),對(duì)含有飽和約束的非線性系統(tǒng)的成果卻非常少。此外,鮮有方法能同時(shí)處理控制輸入的幅值與速率的飽和問題。因此,本文著眼非線性系統(tǒng)的輸入飽和現(xiàn)象,結(jié)合固態(tài)氧化燃料電池(SOFC)、空氣彈性系統(tǒng)和變速風(fēng)力機(jī)(VSWT)等對(duì)象,展開動(dòng)態(tài)抗飽和策略研究。本文的研究內(nèi)容和創(chuàng)新點(diǎn)主要分為以下幾個(gè)部分:1.結(jié)合SOFC考慮非線性離散系統(tǒng),設(shè)計(jì)動(dòng)態(tài)抗飽和策略。首先簡(jiǎn)單介紹了SOFC的基本結(jié)構(gòu)和工作原理,并根據(jù)實(shí)際的控制約束條件來設(shè)計(jì)約束控制器。利用RBF神經(jīng)網(wǎng)絡(luò)來辨識(shí)SOFC的系統(tǒng)模型,得到模型輸入輸出靈敏度函數(shù)。基于BP神經(jīng)網(wǎng)絡(luò)和PID控制設(shè)計(jì)自適應(yīng)控制器,并利用辨識(shí)得到的輸入輸出靈敏度函數(shù)設(shè)計(jì)動(dòng)態(tài)抗飽和補(bǔ)償器。通過抗飽和補(bǔ)償器調(diào)整控制輸入的參考軌跡,達(dá)到抑制輸入飽和的效果,利用Lyapunov函數(shù)進(jìn)行穩(wěn)定性分析,最后結(jié)合SOFC仿真來驗(yàn)證算法的有效性。2.以氣動(dòng)彈性系統(tǒng)為對(duì)象,對(duì)多輸入多輸出非線性離散系統(tǒng)設(shè)計(jì)抗飽和策略。首先簡(jiǎn)單介紹了一種典型的氣動(dòng)彈性系統(tǒng)(二自由度機(jī)翼)的相關(guān)結(jié)構(gòu),利用緊湊型動(dòng)態(tài)線性化(CFDL)對(duì)系統(tǒng)模型進(jìn)行轉(zhuǎn)換。在線性化模型的基礎(chǔ)上,利用多元觀測(cè)器設(shè)計(jì)自適應(yīng)優(yōu)化控制器,將控制問題轉(zhuǎn)化為線性矩陣不等式(LMI)的約束優(yōu)化問題。最后通過仿真驗(yàn)證氣動(dòng)彈性系統(tǒng)控制輸入在約束范圍以內(nèi),并且整個(gè)過程中都不知道這種氣動(dòng)彈性系統(tǒng)的精確模型。3.以VSWT為對(duì)象,研究非線性連續(xù)系統(tǒng)的動(dòng)態(tài)抗飽和策略。先簡(jiǎn)單介紹了一下VSWT的結(jié)構(gòu)和原理,在變換的VSWT模型基礎(chǔ)上,設(shè)計(jì)擴(kuò)展觀測(cè)器估計(jì)系統(tǒng)未知參數(shù),結(jié)合指令濾波器和反步法來設(shè)計(jì)約束控制器,最后通過VSWT的仿真驗(yàn)證算法的有效性。
[Abstract]:In the actual industrial production, the system can not transmit infinite control signal, so the saturation phenomenon exists widely in various systems. However, people often ignore the saturation phenomenon of the system when designing the controller, when the system saturation occurs, The performance of the system decreased significantly. Saturation has caused many tragedies, which make people realize the existence of saturation and its important influence. After a long time of exploration by scholars at home and abroad, saturation constraint control has made great progress. In the past, most of the control methods were based on linear systems, but few results were obtained for nonlinear systems with saturation constraints. In addition, there are few methods to deal with the saturation of input amplitude and rate simultaneously. Therefore, this paper focuses on the input saturation phenomenon of nonlinear systems, and studies the dynamic anti-saturation strategy combined with solid oxide fuel cell (SOFC), air elastic system and variable speed wind turbine (VSWT). The research content and innovation of this paper are divided into the following parts: 1. Considering the nonlinear discrete system, a dynamic anti-saturation strategy is designed. Firstly, the basic structure and working principle of SOFC are briefly introduced, and the constraint controller is designed according to the actual control constraints. The system model of SOFC is identified by RBF neural network, and the sensitivity function of model input and output is obtained. The adaptive controller is designed based on BP neural network and pid control, and the dynamic anti-saturation compensator is designed by using the input and output sensitivity function. The reference trajectory of the control input is adjusted by the anti-saturation compensator to suppress the input saturation. The stability analysis is carried out by using the Lyapunov function. Finally, the effectiveness of the algorithm is verified by the SOFC simulation. An anti-saturation strategy is designed for multi-input and multi-output nonlinear discrete systems based on Aeroelastic systems. In this paper, a typical Aeroelastic system (2-DOF wing) is introduced briefly, and the model of the system is transformed by using compact dynamic linearization (CFDL). Based on the linearization model, an adaptive optimization controller is designed by using a multivariate observer, and the control problem is transformed into a constrained optimization problem of linear matrix inequality (LMI). Finally, the simulation results show that the control input of the Aeroelastic system is within the constraint range, and the exact Aeroelastic system model .3is not known in the whole process. Taking VSWT as an object, the dynamic anti-saturation strategy for nonlinear continuous systems is studied. Firstly, the structure and principle of VSWT are briefly introduced. Based on the transformed VSWT model, an extended observer is designed to estimate the unknown parameters of the system, and a constraint controller is designed by combining the instruction filter and the backstepping method. Finally, the validity of the algorithm is verified by the simulation of VSWT.
【學(xué)位授予單位】：江南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP273

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