【文章內(nèi)容簡介】 itical parameter for robustness in this scheme, a s opposed to the upper bounds of the perturbations themselves. Consequently, the driving terms of the error dynamics are reduced from the uncertainties (as in the conventional SMC) to the accurac y in their estimates. The result is a much better tracking accuracy without being over conservative in control. 在這篇論文中我們提出一個機(jī)電系統(tǒng)中分散震動控制器的設(shè)計方法除了滑 模震動控制器結(jié)構(gòu)和干擾轉(zhuǎn)矩的估算。 估算的精確性是這個計劃中最中堅的評定 參數(shù)，與上面的不確定的范圍正好相反。因此，在評估的精確 性中控制一些誤 差動力學(xué)的條件減少了一些不確定性（就如同在傳統(tǒng)的 SMC 中） 。結(jié)果在沒有 超越傳統(tǒng)的控 制中是一個較好的跟蹤精度。 Experimental robustness properties of fuzzy controllers remain theoretically difficult to prove a nd their synthesis is still an open problem. The nonlinear structure of the final controller is derive d from all controllers at the different stages of fuzzy control, particularly from mon defuzzific ation methods (such as Centre of Area). In general, fuzzy controllers have a regionwise structure given the partition of its input space by the fuzzification stage. Local controls designed in these re gions are then bined into sets to make up the final global control. A partition of the state space can be found for which the controller has regionwise constant parameters. Moreover, each fuzzy controller tuning parameter (. the shapes and the values of input or output variables membership functions) influences the values of parameters in several regions at the same time. In the particula r case of a switching line separating the phase plane into one region where the control is positive whereas in the other it is negative, the fuzzy controller may be seen as a variable structure controll er. This kind of a fuzzy controller can be assimilated to a variable structure controller with bounda ry layer such as in, for which stability theorems exist, but with a nonlinear switching surface. 模糊控制裝置的實驗的健全的性質(zhì)難以用理論去證明它們的綜合仍然是一 個未解決的問題。最終控制器的非線性性質(zhì)來源于各級模糊控制的控制器，顯著 地逆模糊化方法（諸如中心區(qū)） 。通常，模糊控制器有一個區(qū)域勸導(dǎo)的性質(zhì)是模 糊化級數(shù)給的輸入空間。本地控制設(shè)計這些區(qū)域結(jié)合成集使最終的全球控制實 現(xiàn)。一個級 數(shù)空間的分割可以在控制器有區(qū)域勸導(dǎo)的常數(shù)參數(shù)中找到。此外， 每個模糊控制器調(diào)整參數(shù)（即形狀以及輸 入輸出的變量的值的隸屬函數(shù)）會在 同一時間在某些區(qū)域影響參數(shù)的值。在特殊情況下開關(guān)線將相平面分成 一個區(qū) 域 那個區(qū)域中控制是正的反之另一邊是負(fù)的， 模糊控制器可以視為一個可變結(jié)構(gòu) 的控制器。這類的模 糊控制器可以吸收到可變結(jié)構(gòu)控制器邊界層，其中穩(wěn)定性 定理存在，而是一個非線形開關(guān)面。 With the use of trapezoidal input membership functions and appropriate position and infere nce methods, it will be shown that it is possible to obtain rule membership functions which are reg ionwise affine functions of the controller input variable. We propose a linear defuzzification algor ithm that keeps this regionwise affine structure and yields a piecewise affine controller. A particu lar and systematic parameter tuning method will be given which allows turning this controller into a variable structurelike controller. We will pare this regionwise affine controller with a Fuzz y and Variable Structure Controller through the application to an inverted pendulum control. 通過梯形輸入隸屬函數(shù)的使用和適當(dāng)?shù)淖鲌D法和推論方法， 這將說明那是有 可能遵循規(guī)則區(qū)域勸導(dǎo)的輸 入變量仿射函數(shù)的隸屬函數(shù)。我們提出線形逆模糊 化算法它能這個區(qū)域勸導(dǎo)仿射結(jié)構(gòu)和產(chǎn)生一個塊仿射控制 器。一個特殊的系統(tǒng) 的參數(shù)調(diào)節(jié)方法將會被給定它允許把這個控制器調(diào)節(jié)成一個可變的結(jié)構(gòu)相似的 控制器。 我們將比較這個區(qū)域勸導(dǎo)仿射控制器和一個模糊的可變結(jié)構(gòu)的控制器 通過應(yīng)用一個倒立擺控制。 So far, in the application note series, we have provided several examples showing how to create fuzzy controllers with FIDE. However, these examples do not provide topics on implementation o f the designed system. In this application note, we use an example of an inverted pendulum to pro vide details on all aspects of fuzzy logic based system design. 迄今為止，在應(yīng)用筆記系列中，我們已經(jīng)提供了許多展示如何用 FIDE 創(chuàng)造 模糊控制裝置的例子。然而， 這些例子不能提供設(shè)計系統(tǒng)執(zhí)行的話題。在這應(yīng) 用筆記中，我們可以用一個倒