本文關(guān)鍵詞： 風(fēng)力發(fā)電機(jī)組 轉(zhuǎn)矩控制 變槳控制 魯棒-自適應(yīng)控制算法 反步式設(shè)計(jì) Bladed　出處：《北京交通大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著人類社會(huì)的發(fā)展,人類對(duì)于能源的需求急劇增加。然而,傳統(tǒng)能源的減少,能源安全以及全球氣候變暖等問(wèn)題使得人類必須加大對(duì)新型能源的研究。在這樣的背景下,風(fēng)能,作為一種新型的清潔能源日益受到人們的關(guān)注。 本課題研究?jī)?nèi)容是大型風(fēng)力發(fā)電機(jī)組主控系統(tǒng)控制策略,在充分考慮大型風(fēng)力發(fā)電機(jī)組結(jié)構(gòu)、組成的基礎(chǔ)上,設(shè)計(jì)出具有針對(duì)性的大型風(fēng)電機(jī)組主控系統(tǒng),包括轉(zhuǎn)矩控制系統(tǒng),統(tǒng)一變槳控制系統(tǒng),獨(dú)立變槳控制系統(tǒng)以及載荷優(yōu)化系統(tǒng)等。并利用Bladed風(fēng)力發(fā)電機(jī)設(shè)計(jì)仿真軟件對(duì)控制策略進(jìn)行了仿真。 在此基礎(chǔ)上,本文針對(duì)大型風(fēng)機(jī)結(jié)構(gòu)參數(shù)難以獲取的特點(diǎn),重點(diǎn)研究基于魯棒.自適應(yīng)算法。由于常規(guī)的控制方法是完全基于系統(tǒng)參數(shù)模型的控制策略,當(dāng)系統(tǒng)參數(shù)發(fā)生變化或者負(fù)載不定時(shí)的控制效果并不理想。因此,本文針對(duì)風(fēng)機(jī)模型的非線性提出了基于反步設(shè)計(jì)的魯棒自適應(yīng)控制算法。所設(shè)計(jì)控制策略不僅對(duì)系統(tǒng)模型參數(shù)的未知時(shí)變性有較強(qiáng)的魯棒性,而且對(duì)外界環(huán)境引起負(fù)載的干擾有良好的控制效果。并且通過(guò)基于李雅普諾夫穩(wěn)定性證明。 對(duì)于風(fēng)機(jī)系統(tǒng)非線性特性,本文還提出了魯棒-神經(jīng)網(wǎng)絡(luò)算法的風(fēng)機(jī)轉(zhuǎn)矩控制策略。利用神經(jīng)網(wǎng)絡(luò)對(duì)非線性曲線的逼近特性,可以很好地抵消系統(tǒng)非線性特性對(duì)于控制器的不利影響。該方案同魯棒-自適應(yīng)算法相比,對(duì)于控制器輸出的限制較低。該方案的穩(wěn)定性同樣通過(guò)基于李雅普諾夫穩(wěn)定性證明
[Abstract]:With the development of human society, the demand for energy increases rapidly. However, the decrease of traditional energy, energy security and global warming make it necessary for human beings to increase the research on new energy. Wind energy, as a new clean energy, has been paid more and more attention. The main control system control strategy of large wind turbine is studied in this paper. On the basis of fully considering the structure and composition of large wind turbine, the main control system of large wind turbine is designed. It includes torque control system, unified variable propeller control system, independent variable propeller control system and load optimization system. The control strategy is simulated by Bladed wind turbine design simulation software. On this basis, aiming at the difficulty of obtaining the structural parameters of large fan, this paper focuses on the robust and adaptive algorithm. Because the conventional control method is based on the system parameter model, the control strategy is completely based on the system parameter model. The control effect is not ideal when the system parameters change or the load is unscheduled. In this paper, a robust adaptive control algorithm based on backstepping design is proposed for nonlinear fan model. The proposed control strategy is not only robust to unknown time-varying parameters of the system model, but also robust. Moreover, it has a good control effect on the disturbance caused by external environment, and it is proved based on Lyapunov stability. For the nonlinear characteristics of fan system, this paper also proposes a robust neural network algorithm for wind turbine torque control strategy. Compared with the robust adaptive algorithm, the proposed scheme has a lower limit on the controller output. The stability of the scheme is also proved based on Lyapunov stability.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM315;TP273

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本文編號(hào)：1494147