Secondly , the basic theory and algorithm of bp neural network and fuzzy control are presented , and to characteristics of bp neural network and fuzzy logic are discussed respectfully . in this paper a new active control algorithm , the neural network and fuzzy algorithm is proposed by making use of their superiority to the full 然后介紹了bp神經(jīng)網(wǎng)絡(luò)和模糊邏輯的基本原理和算法,分別討論了神經(jīng)網(wǎng)絡(luò)和模糊邏輯的特點(diǎn),分析了各自的優(yōu)點(diǎn)和不足,充分利用了二者的優(yōu)點(diǎn),提出了基于bp神經(jīng)網(wǎng)絡(luò)與模糊邏輯相結(jié)合的結(jié)構(gòu)振動(dòng)控制算法。
According to the special characters of a multi - roll cold tandem mill , a rolling force prediction model based on fuzzy algorithm and cerebellum model articulation controller ( cmac ) combined with the traditional model was designed to improve the precision of rolling force prediction 摘要針對(duì)寬帶鋼多輥冷連軋機(jī)組特點(diǎn),為提高軋制力的預(yù)報(bào)精度,在結(jié)合傳統(tǒng)軋制壓力模型的基礎(chǔ)上把模糊算法和神經(jīng)網(wǎng)絡(luò)有機(jī)結(jié)合,設(shè)計(jì)出基于模糊小腦模型神經(jīng)網(wǎng)絡(luò)的多輥冷連軋機(jī)軋制力預(yù)報(bào)模型。
To overcome the shortcomings of the traditional fuzzy algorithm , including complex management of diagnosis system , high difficulty in improvement and being unfavorable to accumulate experiences , the improved fuzzy algorithm is introduced to the state diagnosis for complex system , the model of state diagnosis for complex system based on the improved fuzzy algorithm is established , and a sample case is adopted to contrast and verify the state diagnosis model based on the traditional fuzzy algorithm and the state diagnosis model for complex system based on the improved fuzzy algorithm respectively , which indicates that although the latter is inferior in the speed of diagnosis , it has the significant advantages in simple management , easiness in improvement , accurate diagnosis , abundant diagnosis information and wide applications , so that its comprehensive performance is far beyond that of the diagnosis model based on traditional fuzzy algorithm 摘要為了克服傳統(tǒng)模糊算法的診斷系統(tǒng)建模復(fù)雜、改進(jìn)難度大、不利于經(jīng)驗(yàn)積累困難的缺點(diǎn),在復(fù)雜系統(tǒng)的狀態(tài)診斷中引入了改進(jìn)的模糊算法,創(chuàng)建了基于改進(jìn)模糊算法的復(fù)雜系統(tǒng)狀態(tài)診斷模型,并以一個(gè)實(shí)例分別比較驗(yàn)證了基于傳統(tǒng)模糊算法的狀態(tài)診斷模型與基于改進(jìn)模糊算法的復(fù)雜系統(tǒng)狀態(tài)診斷模型,結(jié)果表明基于改進(jìn)模糊算法的復(fù)雜系統(tǒng)狀態(tài)診斷模型雖然在診斷速度方面稍遜一籌,但具有建模簡(jiǎn)單、模型改進(jìn)容易、診斷準(zhǔn)確、診斷信息豐富、適用性廣泛等顯著優(yōu)點(diǎn),其綜合性能大大優(yōu)于基于傳統(tǒng)模糊算法的診斷模型。
We mainly discuss the way to design a sensor based on can bus , analyze some fuzzy algorithms and at the same improve an algorithm in order to adapt to the control for large greenhouse , discuss the blocking design method for display , and , at the same time , analyze the configuration design method 作者主要研究了基于can總線技術(shù)的現(xiàn)場(chǎng)總線傳感器的設(shè)計(jì)方法,并設(shè)計(jì)了一款傳感器;分析了幾種模糊控制算法并對(duì)相關(guān)算法作了一些改進(jìn)使之更加適用于溫室大棚的控制;對(duì)圖象顯示的模塊化設(shè)計(jì)方法作了一些探討,同時(shí)對(duì)系統(tǒng)的組態(tài)方法作了一些分析。