本文選題：球磨機(jī) + 大腦情感學(xué)習(xí)模型　； 參考：《江西理工大學(xué)》2017年碩士論文

【摘要】：球磨機(jī)是一種破碎并研磨大塊物料的關(guān)鍵制粉設(shè)備,其具有適用范圍廣、運(yùn)行安全穩(wěn)定、對(duì)物料不挑剔等特點(diǎn),廣泛應(yīng)用于火電廠、礦山、冶金等領(lǐng)域。保證球磨機(jī)能夠安全高效的運(yùn)行,成為了生產(chǎn)單位取得較好經(jīng)濟(jì)效益的關(guān)鍵。然而球磨機(jī)是一個(gè)多變量、強(qiáng)耦合、時(shí)變性的控制對(duì)象,傳統(tǒng)自動(dòng)化控制方法很難實(shí)現(xiàn)對(duì)其較好的控制效果。故而,實(shí)現(xiàn)球磨機(jī)制粉系統(tǒng)的智能化控制具有重要的工程價(jià)值和現(xiàn)實(shí)意義。大腦情感學(xué)習(xí)模型是一種新型的機(jī)器學(xué)習(xí)模型,其模擬大腦的情感和學(xué)習(xí)的機(jī)制,具有較強(qiáng)的學(xué)習(xí)能力和調(diào)節(jié)能力,魯棒性較好。一經(jīng)提出就引起較大關(guān)注,近年來基于大腦情感模型的控制方法已經(jīng)廣泛應(yīng)用在不同的領(lǐng)域。本文圍繞保證球磨機(jī)安全運(yùn)行、提高其工作效率的問題,利用大腦情感學(xué)習(xí)模型對(duì)球磨機(jī)進(jìn)行智能控制,主要內(nèi)容如下:(1)基于球磨機(jī)系統(tǒng)的強(qiáng)耦合、時(shí)變性的特點(diǎn),提出了一種改進(jìn)的大腦情感學(xué)習(xí)模型(brain emotional learning,BEL)的控制方法。采用分?jǐn)?shù)階微積分對(duì)BEL模型的感官輸入函數(shù)和情感暗示函數(shù)進(jìn)行描述,使得BEL模型輸入信號(hào)選擇更為合理,提高了BEL控制器的控制精度。利用多變量逆向解耦的方法,設(shè)計(jì)了基于分?jǐn)?shù)階BEL的智能控制器。仿真結(jié)果表明:該方法具有較好的控制性能、良好的抗干擾性能及模型不敏感,具有良好的魯棒性。(2)為了提高球磨機(jī)控制系統(tǒng)的穩(wěn)定性和控制精度,提出了一種優(yōu)化大腦情感學(xué)習(xí)模型參數(shù)的方法,采用教與學(xué)優(yōu)化算法對(duì)系統(tǒng)的各個(gè)參數(shù)進(jìn)行優(yōu)化,使得系統(tǒng)的各個(gè)參數(shù)更合理,提高了系統(tǒng)的精度。仿真結(jié)果表明:該方法對(duì)參數(shù)選取的精確度較高,能更快尋找到最優(yōu)解。
[Abstract]:Ball mill is a key powder making equipment for crushing and grinding large pieces of material. It has the characteristics of wide application, safe and stable operation, not picky on material and so on. It is widely used in thermal power plant, mine, metallurgy and other fields. To ensure the safe and efficient operation of the ball mill, it has become the key to achieve better economic benefits in the production units. The machine is a multi variable, strong coupling and time-varying control object. The traditional automatic control method is difficult to achieve good control effect. Therefore, it is of great engineering value and practical significance to realize intelligent control of the ball mill pulverizing system. The brain emotion learning model is a new model of machine learning, which simulates the brain. The mechanism of emotion and learning has strong ability to learn and adjust, and has good robustness. Once put forward, it has aroused great concern. In recent years, the control methods based on brain emotion model have been widely used in different fields. This paper focuses on the problem of guaranteeing the safe operation of the ball mill and raising the efficiency of its work, and using the emotional learning of the brain. The main contents of the model are as follows: (1) based on the strong coupling and time-varying characteristics of the ball mill system, an improved brain emotional learning (BEL) control method is proposed. The fractional order calculus is used to describe the sensory input function and the emotional implication function of the BEL model. The input signal selection of the BEL model is more reasonable and the control precision of the BEL controller is improved. By using the multivariable inverse decoupling method, the intelligent controller based on the fractional order BEL is designed. The simulation results show that the method has good control performance, good anti-interference performance and model insensitivity, and has good robustness. (2) (2) In order to improve the stability and control precision of the ball mill control system, a method of optimizing the parameters of the brain emotion learning model is proposed. The parameters of the system are optimized by teaching and learning optimization algorithm. The parameters of the system are more reasonable and the precision of the system is improved. The simulation results show that the accuracy of the method is accurate for the selection of parameters. Higher, can find the optimal solution faster.

【學(xué)位授予單位】：江西理工大學(xué)
【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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