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

【摘要】：控制系統(tǒng)性能監(jiān)測與評價是工業(yè)過程中保證生產(chǎn)運行高效、安全、環(huán)保必不可少的一部分。隨著生產(chǎn)規(guī)模日益擴大,控制回路不斷增多,人工監(jiān)測具有一定難度,必須實現(xiàn)自動的控制系統(tǒng)性能評價及監(jiān)視。目前,火力發(fā)電在我國全社會發(fā)電量中所占比例較大,約為75%左右�；痣姀S設備結(jié)構(gòu)高度復雜,控制回路往往難以實現(xiàn)預期運行效果,需通過一定的評價方法對其性能進行度量,來指導回路中控制器的優(yōu)化。同時,在經(jīng)過一段時間的運行后,原來性能良好的回路由于各種內(nèi)因及外因的影響,性能也會變差,需對其進行及時的監(jiān)視。因此,要想確保良好的運行狀態(tài),進行火電廠控制系統(tǒng)性能評價與優(yōu)化研究十分必要。針對火電廠控制系統(tǒng)性能評價與優(yōu)化問題,本論文的主要工作以及取得成果:首先,針對高斯擾動下的單變量系統(tǒng)介紹了經(jīng)典的最小方差性能評價基準,并將其延伸到多變量控制系統(tǒng)。提出一種基于等效開環(huán)傳遞函數(shù)的多變量控制系統(tǒng)性能評價方法,解決了多變量系統(tǒng)最小方差基準求取復雜、限制條件較多等問題,并由仿真實驗對其實用性以及準確性進行了驗證。其次,針對非高斯噪聲擾動下的系統(tǒng),介紹了最小信息熵性能評價指標,在其基礎上引入有理熵,提出了最小有理熵性能評價指標。同時,介紹了一種基于歷史數(shù)據(jù)的Hellinger距離性能評價基準。通過仿真驗證了最小信息熵指標、最小有理熵指標以及基于Hellinger距離性能指標這三種指標的有效性。通過對比分析,得出基于Hellinger距離性能指標較適合工業(yè)控制系統(tǒng)性能評價,但評價結(jié)果不夠客觀;與最小信息熵指標相比,最小有理熵指標能夠更準確的反映系統(tǒng)性能變化的趨勢這兩點結(jié)論。再次,提出一種標量ITAE性能評價指標用以控制系統(tǒng)確定性性能評價,并將該指標通過子目標乘除法與系統(tǒng)隨機性性能指相標結(jié)合,得到一種綜合性能指標。將綜合指標作為目標函數(shù),對火電廠中的單元機組協(xié)調(diào)控制系統(tǒng)控制器進行參數(shù)優(yōu)化,得到了最優(yōu)自抗擾控制器、廣義預測控制器、內(nèi)模PI控制器參數(shù)與對應最優(yōu)性能指標,并對三種控制器性能進行了對比與監(jiān)測。實驗結(jié)論表明廣義預測控制綜合性能最好,并且在模型參數(shù)攝動情況下魯棒性最好。最后,對于模型參數(shù)未知的火電廠控制系統(tǒng),總結(jié)出一種基于數(shù)據(jù)的綜合性能評價方法,并對貴州省盤南電廠3號機組汽包水位控制回路進行了性能評價與監(jiān)測。
[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.
【學位授予單位】：華北電力大學(北京)
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP273;TM621

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本文編號：1931794