本文關(guān)鍵詞：基于憶阻器的模糊推理系統(tǒng)設(shè)計及應(yīng)用　出處：《西南大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 模糊邏輯 憶阻器 交叉陣列 PID控制 模糊邏輯門

【摘要】：模糊推理系統(tǒng)自提出以來一直被認(rèn)為是一種最接近人腦計算能力的智能系統(tǒng),模糊系統(tǒng)具有推理過程容易理解、專家知識利用較好、對樣本的要求較低等優(yōu)點,但它同時又存在人工干預(yù)多、推理速度慢、精度較低等缺點,很難實現(xiàn)自適應(yīng)學(xué)習(xí)的功能。人工神經(jīng)網(wǎng)絡(luò)具有較強(qiáng)的自學(xué)習(xí)和聯(lián)想功能,用于模擬人腦的思維功能,且人工干預(yù)少,精度較高,但缺點是它不能處理和描述模糊信息,不能很好的利用已有的經(jīng)驗知識,同時它對樣本的要求較高。如果將二者有機(jī)地結(jié)合起來,可起到互補(bǔ)的效果。人腦神經(jīng)元數(shù)量龐大,神經(jīng)元之間連接復(fù)雜,現(xiàn)有的研究大都致力于設(shè)計軟件計算系統(tǒng),難以設(shè)計出與人腦計算能力相匹配的硬件系統(tǒng),亟待提出一種可以擴(kuò)展的簡單硬件來模擬人腦單元。納米級器件憶阻器的提出使類腦硬件電路的實現(xiàn)成為可能。憶阻器是一種無源元件,具有阻值連續(xù)可變,非易失性,快速的開關(guān)轉(zhuǎn)換特性等優(yōu)勢,在關(guān)掉電源后,仍能“記憶”通過的電荷,這與神經(jīng)元突觸的行為類似,可作為神經(jīng)突觸硬件實現(xiàn)的替代物。模糊系統(tǒng)的應(yīng)用領(lǐng)域在不斷擴(kuò)展,因此研究者們都熱衷于找到一種可行的方法來實現(xiàn)一套能夠高速實時運(yùn)行的模糊系統(tǒng)。傳統(tǒng)的模糊系統(tǒng)將語言信息在數(shù)字系統(tǒng)中進(jìn)行處理,隸屬函數(shù)在表示語言變量時轉(zhuǎn)化為二值編碼,而隨著現(xiàn)代科技對計算速度的要求,就需要計算速度更快的模擬電路形式。取大(max)和取小(min)函數(shù)是模糊邏輯里面最重要的部分,如模糊推理就需要取大和取小函數(shù)來確定推理結(jié)果。本文的主要研究內(nèi)容包括以下三個部分。(1)為了提供一種硬件實現(xiàn)類腦計算系統(tǒng)的方案,本文提出一種基于憶阻交叉陣列的模糊推理系統(tǒng),并對復(fù)雜函數(shù)進(jìn)行建模來驗證設(shè)計系統(tǒng)的正確性。首先將傳統(tǒng)的前向人工神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)轉(zhuǎn)換成交叉陣列結(jié)構(gòu),并利用交叉陣列來存儲模糊規(guī)則,構(gòu)造了一種新型模糊推理系統(tǒng),隨后提出了一種基于HP憶阻器交叉陣列結(jié)構(gòu)的模糊推理系統(tǒng)硬件電路設(shè)計方案。當(dāng)輸入數(shù)據(jù)后可以根據(jù)交叉陣列的輸出電壓計算得到模糊推理結(jié)果,最后用所設(shè)計的推理系統(tǒng)對復(fù)雜函數(shù)建模,數(shù)值仿真驗證本文設(shè)計系統(tǒng)的正確性。(2)利用所提出的模糊推理系統(tǒng)設(shè)計了一種基于憶阻交叉陣列的模糊PID控制器,并對典型被控對象進(jìn)行控制,通過數(shù)值仿真得到控制曲面,控制參數(shù)變化過程曲線和控制曲線,證明該系統(tǒng)能正確表示各控制曲面,且響應(yīng)曲線和控制參數(shù)都表明該模糊控制系統(tǒng)表現(xiàn)良好。通過與傳統(tǒng)PID控制和MATALB模糊PID控制工具進(jìn)行對比,也表明所設(shè)計模糊推理系統(tǒng)在PID控制方面的優(yōu)勢,這也為多變量和多維模糊控制器提供了新的研究思路。(3)基于墨滴擴(kuò)散的模糊邏輯原理,利用自旋憶阻器的交叉陣列結(jié)構(gòu)存儲模糊關(guān)系,本文設(shè)計了一種基于自旋憶阻器交叉陣列的模糊邏輯門電路,并用LTSPICE電路仿真驗證了所設(shè)計的模糊門電路的正確性和可行性,此模糊邏輯門電路不僅可以通過更少的步驟實現(xiàn)“與”、“或”、“非”、“異或”等模糊運(yùn)算,且此模糊邏輯門結(jié)構(gòu)簡單,運(yùn)算速度快,硬件實現(xiàn)成本低、體積小、能耗低、應(yīng)用范圍廣,不僅能夠用于傳統(tǒng)的數(shù)字和模擬電路中的各種邏輯門,填補(bǔ)了模糊邏輯門電路的空白,此電路還可以擴(kuò)展到3值和多值的模糊邏輯。為模糊系統(tǒng)及模糊神經(jīng)網(wǎng)絡(luò)硬件實現(xiàn)提供了基礎(chǔ)。
[Abstract]:The fuzzy inference system since it has long been considered an intelligent system closest to the computing ability of the human brain, is easy to understand the reasoning process of fuzzy systems, the use of expert knowledge is good, has the advantages of low sample requirement, but it also has more manual intervention, the inference speed slow, low precision, difficult to achieve adaptive the function of learning. The artificial neural network has strong self-learning and associative function, is used to simulate the human brain thinking function, and less manual intervention, higher precision, but the disadvantage is that it cannot describe fuzzy information processing and use the existing knowledge, experience is not very good, while its sample requirements higher. If the two organically, can play a complementary effect. A large number of neurons, neuron complex connection, most of the existing research devoted to the design calculation software system, it is difficult to design The human brain and the ability to match the computing hardware system, to propose a simple hardware can be extended to simulate the human brain cell. Proposed nanoscale devices memristor that realizes brainlike hardware circuit as possible. Memristor is a passive element, with continuous variable resistance, non-volatile, edge switch the conversion characteristics of fast, turn the power off, still can "charge memory" through this, and synaptic actions are similar, can be used as a substitute for hardware implementation. Synaptic fuzzy system used in the field of continuous expansion, so researchers are keen to find a feasible method to achieve a set of can the fuzzy system of high speed. The traditional fuzzy system of language information processing in digital system, the membership functions in the representation language variables into two value encoding, and with modern science and technology on computing speed The request requires faster calculation speed. Taking the form of analog circuit (max) and small (min) function is the most important part of fuzzy logic, such as fuzzy inference requires large and small function to determine the reasoning results. The main contents of this paper include the following three parts. (1 in order to realize the brain like computing system) provides a hardware scheme, this paper proposes a fuzzy inference system based on memristive crossbar array, and the complex functions are modeled to verify the correctness of the design system. Firstly, the traditional feedforward artificial neural network, structural transfer into cross array structure, and using the cross array to store the fuzzy rules, to construct a new fuzzy inference system, and then proposes a fuzzy inference system hardware circuit design of HP memory array structure based on cross resistance. When the input data can be based on cross array The output voltage is calculated by fuzzy reasoning results, finally the inference system design of complex function modeling, numerical simulation to verify the correctness of the design of the system. (2) using fuzzy inference system is proposed to design a fuzzy PID controller based on memristor crossbar array, and the typical controlled object control, control surface through numerical simulation, the control parameter curves and control curve shows that the system can correctly represent the control surfaces, and the response curves and control parameters show that the fuzzy control system. Through good performance with the traditional PID control and fuzzy PID control MATALB tools comparison, also showed that the design of fuzzy inference system in PID control the advantage of this is a multi variable and multi dimension fuzzy controller provides a new research idea. (3) the fuzzy logic principle of droplet diffusion based on the use of spin memristor Cross array memory fuzzy relation, this paper designs a fuzzy logic gate circuit spin memristor based on cross array, and the design of fuzzy circuit correctness and feasibility is proved by the LTSPICE simulation, the fuzzy logic gate circuit can not only through fewer steps to achieve the "and" and "or", "not", "XOR" fuzzy operation, and the fuzzy logic has the advantages of simple structure, fast calculation speed, hardware implementation of low cost, small volume, low energy consumption, wide application range, not only can be used for various types of logic gates the traditional analog and digital circuit, to fill the gaps in the fuzzy logic gate circuit, this circuit can also be extended to more than 3 of the value of fuzzy logic and fuzzy value. The fuzzy neural network system and the hardware implementation provides the basis.

【學(xué)位授予單位】：西南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP18;TP273

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本文編號：1397867