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

【摘要】：在實際的工業(yè)生產中,系統(tǒng)不能傳輸無限大的控制信號,所以飽和現象廣泛存在于各種系統(tǒng)中,然而人們在設計控制器時往往會忽略系統(tǒng)的飽和現象,當系統(tǒng)發(fā)生飽和時,系統(tǒng)性能顯著下降。飽和現象曾引起了許多悲劇,這些悲劇讓人們開始意識到飽和的存在及其重要影響。經過國內外學者長時間的探索,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)的輸入飽和現象,結合固態(tài)氧化燃料電池(SOFC)、空氣彈性系統(tǒng)和變速風力機(VSWT)等對象,展開動態(tài)抗飽和策略研究。本文的研究內容和創(chuàng)新點主要分為以下幾個部分:1.結合SOFC考慮非線性離散系統(tǒng),設計動態(tài)抗飽和策略。首先簡單介紹了SOFC的基本結構和工作原理,并根據實際的控制約束條件來設計約束控制器。利用RBF神經網絡來辨識SOFC的系統(tǒng)模型,得到模型輸入輸出靈敏度函數�；贐P神經網絡和PID控制設計自適應控制器,并利用辨識得到的輸入輸出靈敏度函數設計動態(tài)抗飽和補償器。通過抗飽和補償器調整控制輸入的參考軌跡,達到抑制輸入飽和的效果,利用Lyapunov函數進行穩(wěn)定性分析,最后結合SOFC仿真來驗證算法的有效性。2.以氣動彈性系統(tǒng)為對象,對多輸入多輸出非線性離散系統(tǒng)設計抗飽和策略。首先簡單介紹了一種典型的氣動彈性系統(tǒng)(二自由度機翼)的相關結構,利用緊湊型動態(tài)線性化(CFDL)對系統(tǒng)模型進行轉換。在線性化模型的基礎上,利用多元觀測器設計自適應優(yōu)化控制器,將控制問題轉化為線性矩陣不等式(LMI)的約束優(yōu)化問題。最后通過仿真驗證氣動彈性系統(tǒng)控制輸入在約束范圍以內,并且整個過程中都不知道這種氣動彈性系統(tǒng)的精確模型。3.以VSWT為對象,研究非線性連續(xù)系統(tǒng)的動態(tài)抗飽和策略。先簡單介紹了一下VSWT的結構和原理,在變換的VSWT模型基礎上,設計擴展觀測器估計系統(tǒng)未知參數,結合指令濾波器和反步法來設計約束控制器,最后通過VSWT的仿真驗證算法的有效性。
[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.
【學位授予單位】：江南大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP273

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本文編號：2115102