本文選題：振動(dòng)主動(dòng)控制 + 自適應(yīng)控制　； 參考：《上海大學(xué)》2014年博士論文

【摘要】：振動(dòng)主動(dòng)控制涉及到結(jié)構(gòu)動(dòng)力學(xué)、聲學(xué)、材料科學(xué)技術(shù)、電子信息與技術(shù)、控制科學(xué)與工程等諸多學(xué)科,是目前振動(dòng)工程領(lǐng)域最重要的研究方向。作為振動(dòng)主動(dòng)控制研究的核心內(nèi)容,當(dāng)前振動(dòng)主動(dòng)控制方法及其算法的研究如火如荼,近乎包含了所有現(xiàn)存的控制理論方法與控制技術(shù)。但總體而言,多數(shù)的控制方法和技術(shù)多多少少都存在適用性和實(shí)踐性的問題,目前學(xué)術(shù)界還沒有提出一種能夠適用于多數(shù)振動(dòng)主動(dòng)控制系統(tǒng)控制器設(shè)計(jì)的范式方法與技術(shù),相關(guān)的理論方法和技術(shù)均亟待進(jìn)一步的深入研究與探索。 基于國家自然科學(xué)基金重大研究計(jì)劃科研課題背景,圍繞“在保證受控系統(tǒng)穩(wěn)定的基礎(chǔ)上,提高整個(gè)振動(dòng)主動(dòng)控制系統(tǒng)的魯棒性與控制性能”這一核心問題,本文選取當(dāng)前研究熱點(diǎn)之一的自適應(yīng)振動(dòng)主動(dòng)控制方法與技術(shù)為切入點(diǎn),著重面向自適應(yīng)前饋振動(dòng)控制方法與自適應(yīng)混合振動(dòng)控制方法,進(jìn)行相關(guān)方法研究、控制算法推導(dǎo)、算法分析與實(shí)驗(yàn)驗(yàn)證工作。在理論方法上給出相關(guān)控制算法的穩(wěn)定性與收斂性分析范式方法,在技術(shù)方法上給出相關(guān)控制算法實(shí)施的一般技術(shù)指引。論文主要研究工作與學(xué)術(shù)貢獻(xiàn)如下： (1)使用慣性作動(dòng)器作為抑振作動(dòng)器與模擬擾動(dòng)作動(dòng)器,使用加速度傳感器作為參考傳感器與殘差傳感器,構(gòu)建具有典型機(jī)械結(jié)構(gòu)振動(dòng)正反饋的實(shí)驗(yàn)平臺(tái)和實(shí)驗(yàn)環(huán)境。形成一套半實(shí)物振動(dòng)主動(dòng)控制仿真分析與實(shí)時(shí)振動(dòng)主動(dòng)控制實(shí)驗(yàn)平臺(tái),用于實(shí)現(xiàn)面向工程應(yīng)用的振動(dòng)主動(dòng)控制方法研究與驗(yàn)證。 (2)針對(duì)現(xiàn)有參數(shù)自適應(yīng)算法的局限性,研究和導(dǎo)出一種范式改進(jìn)型遞推最小二乘算法；給出長時(shí)間實(shí)時(shí)自適應(yīng)控制過程中,使用U-D分解技術(shù)更新自適應(yīng)增益矩陣的具體過程與詳細(xì)方法。 (3)針對(duì)振動(dòng)主動(dòng)控制系統(tǒng)面臨的系統(tǒng)辨識(shí)問題,研究和推導(dǎo)遞推最小二乘算法、擴(kuò)展遞推最小二乘算法和擴(kuò)展預(yù)測(cè)模型輸出誤差算法等三種辨識(shí)方法。確定白化測(cè)試校驗(yàn)準(zhǔn)則與模型校驗(yàn)方法,給出振動(dòng)主動(dòng)控制系統(tǒng)參數(shù)辨識(shí)的一般方法與技術(shù)流程。 (4)基于改進(jìn)型遞推最小二乘參數(shù)自適應(yīng)算法族,提出自適應(yīng)前饋振動(dòng)主動(dòng)控制算法的范式描述方法；基于超穩(wěn)定性理論,給出了完整的控制算法推導(dǎo)過程與算法分析過程。通過分析給出了確定環(huán)境下算法穩(wěn)定與隨機(jī)環(huán)境下算法收斂的嚴(yán)格正實(shí)條件,以及相應(yīng)的放松嚴(yán)格正實(shí)條件的要求。針對(duì)確定環(huán)境滿足完美匹配條件、隨機(jī)環(huán)境滿足完美匹配條件以及不滿足完美匹配條件的情況,分別給出了相關(guān)控制算法的仿真算例。仿真結(jié)果表明：通過引入特定的預(yù)濾波器,能夠顯著改善自適應(yīng)前饋振動(dòng)控制算法的控制效果；在測(cè)量環(huán)境存在較大噪聲時(shí)以及參數(shù)數(shù)目不能滿足完美匹配條件時(shí),所給出的自適應(yīng)前饋振動(dòng)控制算法依然有效,同時(shí)具有優(yōu)良的抑振效果與收斂性能。 (5)為改善單純前饋?zhàn)赃m應(yīng)振動(dòng)控制算法的收斂性能與控制效果,推導(dǎo)了一種基于混合自適應(yīng)控制算法的振動(dòng)主動(dòng)控制方法,提出了混合自適應(yīng)振動(dòng)主動(dòng)控制算法的范式描述與分析方法,給出了完整的自適應(yīng)混合振動(dòng)控制算法的推導(dǎo)過程與算法分析過程。通過分析給出了確定環(huán)境下算法穩(wěn)定與隨機(jī)環(huán)境下算法收斂的嚴(yán)格正實(shí)條件,以及相應(yīng)的放松嚴(yán)格正實(shí)條件的要求。同樣針對(duì)確定環(huán)境滿足完美匹配條件、隨機(jī)環(huán)境滿足完美匹配條件以及不滿足完美匹配條件的情況,分別給出了相關(guān)控制算法的仿真算例。仿真結(jié)果表明：混合自適應(yīng)控制器能夠有效改善前饋?zhàn)赃m應(yīng)振動(dòng)控制器的性能,以更少的控制器階次,得到更佳的控制效果。 (6)針對(duì)所提出的自適應(yīng)前饋振動(dòng)控制算法、自適應(yīng)混合振動(dòng)控制算法進(jìn)行實(shí)驗(yàn)分析與驗(yàn)證工作,并將相關(guān)結(jié)果與前饋FULMS算法、混合FULMS算法予以比較。相關(guān)實(shí)驗(yàn)結(jié)果表明：基于改進(jìn)型遞推最小二乘參數(shù)自適應(yīng)算法族的所有前饋振動(dòng)控制算法,其控制效果均明顯優(yōu)于前饋FULMS算法；基于改進(jìn)型遞推最小二乘參數(shù)自適應(yīng)算法族的所有混合自適應(yīng)振動(dòng)控制算法,其控制效果均明顯優(yōu)于混合FULMS算法、結(jié)合極點(diǎn)配置反饋的混合前饋?zhàn)赃m應(yīng)控制算法,以及基于改進(jìn)型遞推最小二乘參數(shù)自適應(yīng)算法族的前饋振動(dòng)控制算法。
[Abstract]:Active vibration control, which involves structural dynamics, acoustics, material science and technology, electronic information and technology, control science and engineering, is the most important research direction in the field of vibration engineering. As the core content of the active vibration control research, the current research on the main vibration control method and its algorithm is in full swing. All the existing control theory methods and control techniques are included, but in general, most of the control methods and techniques are both practical and practical. At present, the academic circle has not put forward a paradigm and technique that can be applied to most of the controller design of the active vibration control system. The technology needs further research and exploration.
Based on the background of the scientific research project of the National Natural Science Foundation of China, this paper focuses on the core problem of "improving the robustness and control performance of the whole vibration active control system on the basis of ensuring the stability of the controlled system". This paper selects the adaptive vibration active control method and technology as one of the hot spots in the current research. The adaptive forward feed vibration control method and the adaptive hybrid vibration control method are used to study the related methods, the control algorithm derivation, the algorithm analysis and the experimental verification. In the theoretical method, the stability and convergence analysis paradigm method of the related control algorithm is given, and the general implementation of the related control algorithm is given in the technical method. The main research work and academic contributions are as follows:
(1) using an inertial actuator as an anti vibration actuator and an analogue actuator, the acceleration sensor is used as a reference sensor and a residual sensor, the experimental platform and the experimental environment for the positive feedback of a typical mechanical structure vibration are constructed. A set of simulation analysis for the active control system of the semi physical vibration and the experiment of active control of the real time vibration are formed. The platform is used to research and verify the active vibration control method for engineering application.
(2) in view of the limitations of the existing parameter adaptive algorithm, a new type of recursion least squares algorithm is developed and derived. The specific process and detailed method of updating adaptive gain matrix using U-D decomposition technique in the process of long time adaptive control are given.
(3) aiming at the system identification problem of the active vibration control system, we study and deduce the recursive least square algorithm, expand the three identification methods, such as the recursive least square algorithm and the output error algorithm of the extended prediction model, and determine the whitening test verification criterion and the model verification method, and give the general square of the parameter identification of the active vibration control system. The process of law and technology.
(4) based on the improved recursive least square parameter adaptive algorithm family, a paradigm description method of adaptive feedforward vibration active control algorithm is proposed. Based on the super stability theory, the complete control algorithm derivation process and the algorithm analysis process are given. The algorithm convergence under the environment and random environment is given by analysis. In order to determine the perfect match condition of the environment, the random environment satisfies the perfect matching condition and the condition that the perfect match is not satisfied, the simulation example of the correlation control algorithm is given. The simulation results show that the specific prefilter is introduced. The adaptive feedforward vibration control algorithm can significantly improve the control effect of the adaptive feedforward vibration control algorithm. When the measurement environment has large noise and the number of parameters can not meet the perfect matching condition, the adaptive feedforward vibration control algorithm is still effective, and it has excellent vibration suppression effect and convergence performance.
(5) in order to improve the convergence performance and control effect of the simple feedforward adaptive vibration control algorithm, a vibration active control method based on the hybrid adaptive control algorithm is derived. The model description and analysis method of the hybrid adaptive vibration active control algorithm is proposed, and the complete adaptive hybrid vibration control algorithm is derived. The process and algorithm analysis process. Through the analysis, the strict positive real conditions of algorithm convergence under the environment algorithm stability and random environment are given, as well as the corresponding requirements for the relaxation of strict positive real conditions. It is also aimed at satisfying the perfect matching conditions for the environment to meet the perfect matching conditions, and the random environment satisfies the perfect matching condition and does not satisfy the perfect matching condition. The simulation results show that the hybrid adaptive controller can effectively improve the performance of the feedforward adaptive vibration controller, with less controller order and better control effect.
(6) in view of the proposed adaptive feedforward vibration control algorithm, the adaptive hybrid vibration control algorithm is used for experimental analysis and verification, and the correlation results are compared with the feedforward FULMS algorithm and the hybrid FULMS algorithm. The experimental results show that all the feedforward vibration control based on the improved recursive minimum two multiplication parameter adaptive algorithm is based on the experimental results. The control effect of the algorithm is obviously better than the feedforward FULMS algorithm, and all the hybrid adaptive vibration control algorithms based on the improved recursive least squares parameter adaptive algorithm are obviously better than the hybrid FULMS algorithm, combined with the hybrid feedforward adaptive control algorithm with the pole assignment feedback, and the improved recursive algorithm. Feedforward vibration control algorithm for small multiplicative parameter adaptive algorithm family.
【學(xué)位授予單位】：上海大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB535

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本文編號(hào)：1924834