【正文】 jek39。s fuzzy control system uses 12 inputs: 6 to obtain the current clarity data provided by the CCD and 6 to measure the rate of change of lens movement. The output is the position of the lens. The fuzzy control system uses 13 rules and requires kilobytes of memoryAs another example of a practical system, an industrial air conditioner designed by Mitsubishi uses 25 heating rules and 25 cooling rules. A temperature sensor provides input, with control outputs fed to an inverter, a pressor valve, and a fan motor. Compared to the previous design, the fuzzy controller heats and cools five times faster, reduces power consumption by 24%, increases temperature stability by a factor of two, and uses fewer sensors. The enthusiasm of the Japanese for fuzzy logic is reflected in the wide range of other applications they have investigated or implemented: character and handwriting recognition。嚴謹的邏輯正當化中給出的模糊控制 Hajek的書 ,被描繪成一個模糊控制理論的基本 Hajek邏輯。 。在理論上有幾十個 ,每個都有各種各樣的優(yōu)點和缺點?！胺浅！?,因為一個典型的例子 ,廣場隸屬函數 。 作為討論之前 ,加工階段是基于規(guī)則的集合的形式邏輯 IF THEN 報表 ,那里的部分叫做“之前”和后來的部分被稱為“隨之”。在許多情況下 ,模糊控制可以用來改善現有的傳統(tǒng)控制器系統(tǒng)通過增加了額外的情報電流控制方法。這個結果將被映射成一個隸屬函數和控制輸出變量的真值。 模糊集 輸入變量在一個模糊控制系統(tǒng)是集映射到一般由類似的隸屬度函數 ,稱為“模糊集”。美國環(huán)境保護署分析了模糊控制節(jié)能電動機 ,美國國家航空和宇宙航行局研究了模糊控制自動太空對接。相機的模糊控制系統(tǒng)采用 12 輸入 ,6 個輸入了解解現行清晰所提供的數據和其他 6 個輸入測量 CCD 鏡頭的變化率的運動。該系統(tǒng)在兩種情況下 ,保持穩(wěn)定。 模糊系統(tǒng)在很大程度上在美國被忽略了 ,因為他們更多關注的是人工智能 ,一個被過分吹噓的領域 ,尤其是在 1980 年中期年代 ,導致在誠信缺失的商業(yè)領域。模糊控制理論 畢業(yè)設計 (論文 )外文文獻翻譯 模糊控制理論 摘自 維基百科 2021 年 11 月 20 日 概述 模糊邏輯廣泛適用于機械控制。 然而日本人對 這個卻沒有偏見和忽略 ,模糊系統(tǒng)引發(fā)日立的 Seiji Yasunobu 和 Soji Yasunobu Miyamoto 的興趣。 Yamakawa 最終繼續(xù)組織自己的 fuzzysystems 研究實驗室?guī)椭米约旱膶＠谔锏乩锏臅r候。輸出的位置是鏡頭。 仿真結果表明 ,模糊控制系統(tǒng)可大大降低燃料消耗。轉換的過程中 ,一個干脆利落的輸入值模糊值稱為“模糊化”。 這些結果相結合 ,給出了具體的“脆”的答案 ,實際的制動壓力 ,一 個過程被稱為解模糊化 ,結合了模糊操作規(guī)則 推理“描述”模糊專家系統(tǒng)”。 模糊控的細節(jié) 模糊控制器是很簡單的理念上。典型的模糊控制系統(tǒng)具有幾十個規(guī)則。因為會員價值總是小于 1,這減少了隸屬函數。 “質心”的方法很受歡迎 ,在“的質心”的結果提供了清新的價值。 測試套件驗證通過制度 ,調整細節(jié)的要求。在 2021 Gerla 模糊控制邏輯方法 ,提出了一種基于以下的想法。 optical fuzzy systems。s book ,where fuzzy control is represented as a theory of H225。s operational specifications and inputs and the fuzzy sets for the the rule the defuzzification through test suite to validate system, adjust details as required6plete document and release to production. Logical interpretation of fuzzy control In spite of the appearance there are several difficulties to give a rigorous logical interpretation of the IFTHEN rules. As an example, interpret a rule as IF temperature is cold THEN heater is high by the first order formula Coldx→ Highy and assume that r is an input such that Coldr is false. Then the formula Coldr→ Hight is true for any t and therefore any t gives a correct control given r. Obviously, if we consider systems of rules in which the class antecedent define a partition such a paradoxical phenomenon does not arise. In any case it is sometimes unsatisfactory to consider two variables x and y in a rule without some kind of functional dependence. A rigorous logical justification of fuzzy control is given in H225。 Fuzzy Control From Wikipedia20 November 2021 Overview Fuzzy logic is widely used in machine control. The term itself inspires a certain skepticism, sounding equivalent to halfbaked logic or bogus logic, but the fuzzy part does not refer to a lack of rigour in the method, rather to the fact that the logic involved can deal with concepts that cannot be expressed as true or false but rather as partially true. Although geic algorithms and neural works can perform just as well as fuzzy logic in many cases, fuzzy logic has the advantage that the solution to the problem can be cast in terms that human oper