本文選題：性能評(píng)價(jià) + 多變量系統(tǒng)　； 參考：《華北電力大學(xué)(北京)》2017年碩士論文

【摘要】：控制系統(tǒng)性能監(jiān)測(cè)與評(píng)價(jià)是工業(yè)過(guò)程中保證生產(chǎn)運(yùn)行高效、安全、環(huán)保必不可少的一部分。隨著生產(chǎn)規(guī)模日益擴(kuò)大,控制回路不斷增多,人工監(jiān)測(cè)具有一定難度,必須實(shí)現(xiàn)自動(dòng)的控制系統(tǒng)性能評(píng)價(jià)及監(jiān)視。目前,火力發(fā)電在我國(guó)全社會(huì)發(fā)電量中所占比例較大,約為75%左右�；痣姀S設(shè)備結(jié)構(gòu)高度復(fù)雜,控制回路往往難以實(shí)現(xiàn)預(yù)期運(yùn)行效果,需通過(guò)一定的評(píng)價(jià)方法對(duì)其性能進(jìn)行度量,來(lái)指導(dǎo)回路中控制器的優(yōu)化。同時(shí),在經(jīng)過(guò)一段時(shí)間的運(yùn)行后,原來(lái)性能良好的回路由于各種內(nèi)因及外因的影響,性能也會(huì)變差,需對(duì)其進(jìn)行及時(shí)的監(jiān)視。因此,要想確保良好的運(yùn)行狀態(tài),進(jìn)行火電廠控制系統(tǒng)性能評(píng)價(jià)與優(yōu)化研究十分必要。針對(duì)火電廠控制系統(tǒng)性能評(píng)價(jià)與優(yōu)化問(wèn)題,本論文的主要工作以及取得成果:首先,針對(duì)高斯擾動(dòng)下的單變量系統(tǒng)介紹了經(jīng)典的最小方差性能評(píng)價(jià)基準(zhǔn),并將其延伸到多變量控制系統(tǒng)。提出一種基于等效開(kāi)環(huán)傳遞函數(shù)的多變量控制系統(tǒng)性能評(píng)價(jià)方法,解決了多變量系統(tǒng)最小方差基準(zhǔn)求取復(fù)雜、限制條件較多等問(wèn)題,并由仿真實(shí)驗(yàn)對(duì)其實(shí)用性以及準(zhǔn)確性進(jìn)行了驗(yàn)證。其次,針對(duì)非高斯噪聲擾動(dòng)下的系統(tǒng),介紹了最小信息熵性能評(píng)價(jià)指標(biāo),在其基礎(chǔ)上引入有理熵,提出了最小有理熵性能評(píng)價(jià)指標(biāo)。同時(shí),介紹了一種基于歷史數(shù)據(jù)的Hellinger距離性能評(píng)價(jià)基準(zhǔn)。通過(guò)仿真驗(yàn)證了最小信息熵指標(biāo)、最小有理熵指標(biāo)以及基于Hellinger距離性能指標(biāo)這三種指標(biāo)的有效性。通過(guò)對(duì)比分析,得出基于Hellinger距離性能指標(biāo)較適合工業(yè)控制系統(tǒng)性能評(píng)價(jià),但評(píng)價(jià)結(jié)果不夠客觀;與最小信息熵指標(biāo)相比,最小有理熵指標(biāo)能夠更準(zhǔn)確的反映系統(tǒng)性能變化的趨勢(shì)這兩點(diǎn)結(jié)論。再次,提出一種標(biāo)量ITAE性能評(píng)價(jià)指標(biāo)用以控制系統(tǒng)確定性性能評(píng)價(jià),并將該指標(biāo)通過(guò)子目標(biāo)乘除法與系統(tǒng)隨機(jī)性性能指相標(biāo)結(jié)合,得到一種綜合性能指標(biāo)。將綜合指標(biāo)作為目標(biāo)函數(shù),對(duì)火電廠中的單元機(jī)組協(xié)調(diào)控制系統(tǒng)控制器進(jìn)行參數(shù)優(yōu)化,得到了最優(yōu)自抗擾控制器、廣義預(yù)測(cè)控制器、內(nèi)模PI控制器參數(shù)與對(duì)應(yīng)最優(yōu)性能指標(biāo),并對(duì)三種控制器性能進(jìn)行了對(duì)比與監(jiān)測(cè)。實(shí)驗(yàn)結(jié)論表明廣義預(yù)測(cè)控制綜合性能最好,并且在模型參數(shù)攝動(dòng)情況下魯棒性最好。最后,對(duì)于模型參數(shù)未知的火電廠控制系統(tǒng),總結(jié)出一種基于數(shù)據(jù)的綜合性能評(píng)價(jià)方法,并對(duì)貴州省盤南電廠3號(hào)機(jī)組汽包水位控制回路進(jìn)行了性能評(píng)價(jià)與監(jiān)測(cè)。
[Abstract]:The performance monitoring and evaluation of control system is an essential part to ensure high efficiency, safety and environmental protection in industrial process. With the increasing scale of production and the increasing number of control loops, manual monitoring is difficult, so it is necessary to realize automatic performance evaluation and monitoring of the control system. At present, the proportion of thermal power generation in the whole society is about 75%. The structure of thermal power plant equipment is highly complex and the control loop is often difficult to achieve the expected operation effect. It is necessary to measure its performance by a certain evaluation method to guide the optimization of the controller in the loop. At the same time, after running for a period of time, the performance of the original circuit with good performance will become poor due to various internal and external factors, so it needs to be monitored in time. Therefore, in order to ensure good operation state, it is necessary to evaluate and optimize the performance of thermal power plant control system. Aiming at the performance evaluation and optimization of control system in thermal power plant, the main work and achievements of this paper are as follows: firstly, the classical minimum variance performance evaluation benchmark is introduced for the single-variable system under Gao Si disturbance. It is extended to multivariable control system. A performance evaluation method for multivariable control systems based on equivalent open loop transfer function is proposed. The practicability and accuracy are verified by simulation experiments. Secondly, the performance evaluation index of minimum information entropy is introduced for the system with non-Gao Si noise disturbance. Based on the introduction of rational entropy, the performance evaluation index of minimum rational entropy is proposed. At the same time, a Hellinger distance performance evaluation benchmark based on historical data is introduced. The effectiveness of the minimum information entropy index, the minimum rational entropy index and the performance index based on Hellinger distance are verified by simulation. Through comparison and analysis, it is concluded that the performance index based on Hellinger distance is more suitable for the performance evaluation of industrial control system, but the evaluation result is not objective enough, and compared with the minimum information entropy index, The minimum rational entropy index can reflect the trend of system performance change more accurately. Thirdly, a scalar ITAE performance evaluation index is proposed to control the deterministic performance evaluation of the system, and a comprehensive performance index is obtained by combining the sub-objective multiplication and division method with the stochastic performance index of the system. Taking the comprehensive index as the objective function, the parameters of the coordinated control system controller of the unit in the thermal power plant are optimized, and the parameters of the optimal ADRC controller, the generalized predictive controller, the internal model Pi controller and the corresponding optimal performance index are obtained. The performance of the three controllers is compared and monitored. The experimental results show that the generalized predictive control has the best comprehensive performance and the best robustness under the perturbation of the model parameters. Finally, for the control system of thermal power plant with unknown model parameters, a comprehensive performance evaluation method based on data is summarized, and the performance evaluation and monitoring of drum water level control loop of No. 3 unit in Pannan Power Plant, Guizhou Province are carried out.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP273;TM621

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