【正文】 hmproposevariable.controllerofaffinewhich aremembershipobtainpossibleitshownwillmethods,positionandmembershiptrapezoidaluse Withtheoscillationsforvalidmodelinghencelinear system,asispendulumtheinverted Modelingsoextent,towhichone,thanwhetherinverypenduluman effective pendulum stabilization. Thus thehencecontroller,ofgooda correct scheduling of each task is crucial forobviousIttheschedulinghow these tasks are activated (. The activation order) isThedifferentcooperatingofaActually the algorithm is implement form the numerical point of viewthealgorithm,statespaceunderlyingthe performance of thevaliditytestbenchmark,asisInverted Thefuzzyspacecontrollers,different controllersperformanceshowexperimentssimulationsuseditcontrolled system.ofnor(neithertraditionalisinvertedreconstruct39。systempotentiometers).through(obtainedpendulumandthe horizontalvaluesthecalculatedtoforceThe pendulum39。contrasttendsforcemotorthroughtheexertingis possibleposition.toponpendulumstabilizeisthegoalunsteady equilibrium.TheAn inverted pendulum is a physical device consisting in a cylindrical bar (usuallypendulum, modeling, PIDc(t) to x(t) in Figure 3.The poles at the origin makes the system subject to drift. With these integrators, Murphy39。 which eventually lead the poles into the right half plane). Thus we use a pensatorand we assume that . The block diagram of the system is shown in Figure 3,and the root locus plot bees as in Figure 4 (note that since there is an inversion in G(s),we draw the block diagram with a positive summing junction).Figure 3: Block diagram of the pensated systemFigure 4: Rootlocus plot of pendulum with integrating pensator，L(s) = K(s)M(s)G(s)Siebert explains that a physical interpretation for the need for this integrator arises from the fact that we are using a voltagecontrolled motor. Without the integrator a constant angular error only achieves a constant cart velocity, which is not enough to make the pendulum upright. In order to get underneath the pendulum, the cart must be accelerated。 and177。 (otherwise, the asymptotes would be 177。. Including the familiar motor transfer function Figure 2: Rootlocus plot of pendulum and motor, L(s) = M(s)G(s)with the plant G(s), we get a root locus with one pole that stays in the right halfplane. Using normalized numbers, we get the root locus plot as is seen in Figure 2.In order to stabilize the system, we need to get rid of the remaining zero at the origin so that the locus from the plant pole on the positive real axis moves into the left halfplane. Thus our pensator must include a pole at the origin. However, we should balance the added pensator pole with an added zero, so that the number of poles less the number of zeros remains equal to two, leaving the rootlocus asymptotes at 177。原文一：The Inverted Pendulum SystemThe inverted pendulum system is a popular demonstration of using feedback control to stabilize an openloop unstable system. The first solution to this problem was described by Roberge [1] in his aptly named thesis, The Mechanical Seal. Subsequently, it has been used in many books and papers as an example of an unstable system.Siebert [2, pages 177~182] does a plete analysis of this system using the Routh Criterion, by multiplying out the characteristic equation as a polynomial of s and studying the coefficients. Although correct, this approach is unnecessarily abstruse. This system is the ideal rootlocus analysis example.Figure 1: Geometry of the inverted pendulum systemConsider the inverted pendulum system in Figure 1. At a pendulum angle of 181。工業(yè)的案例學習，介紹了滑?？刂茍?zhí)行的Matlab軟件。從這些基礎中，許多先進的理論的成果在不斷發(fā)展。 我們將提供讀者一個徹底的滑模控制領域的基礎并且適合大學生使用的經(jīng)典控制理論和一寫狀態(tài)空間方控制規(guī)則的選擇該規(guī)則將使開關(guān)方程在系統(tǒng)狀態(tài)中變得有價值。第一個包括開關(guān)方程的設計所以滑行的動作滿足設計規(guī)范。另外，立即指定性能的能力使得滑?？刂茝脑O計觀點看變得有價值。這種方法有兩個主要的優(yōu)點：第一，系統(tǒng)的動態(tài)性能適應于開關(guān)方程的特殊選擇；第二，閉環(huán)響應完全不受不確定的特殊種類的影響。 前蘇聯(lián)在20世紀50年代末最先開始利用這些自然的想法。介紹這個額外的系統(tǒng)的復雜性的優(yōu)勢之一就是可以將系統(tǒng)中復合結(jié)構(gòu)的有用的性質(zhì)組合起來。一個可變結(jié)構(gòu)系統(tǒng)，被認為是各子系統(tǒng)的結(jié)合其中每個子系統(tǒng)有一個確定的控制結(jié)構(gòu)并且結(jié)果是對系統(tǒng)結(jié)構(gòu)決策規(guī)則，條件是開關(guān)方程，將輸入估計成正確的系統(tǒng)特性并且產(chǎn)生一個輸出精確的反饋控制器使之可以及滑模控制是可變結(jié)構(gòu)控制系統(tǒng)（VSCS）的一個特殊的類型。堅固的操縱控制器設計的一這已經(jīng)導致了工程師這種如何使用這個曲線去定義標志還有變量的隸屬函數(shù)，還有就是如何為控制器創(chuàng)立一套規(guī)則。我們將描繪一個控制曲線當使用模糊控制裝置時它與一個常規(guī)控制器是如何的不同。隨后我們將展示如何為系統(tǒng)設計一個模糊控制裝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。一個區(qū)域那個區(qū)域中控制是正的反之另一邊是負的，模糊控制器可以視為一個可變結(jié)構(gòu)的控制器。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。數(shù)空間的分割可以在控制器有區(qū)域勸導的常數(shù)參數(shù)中找到。本地控制設計這些區(qū)域結(jié)合成集使最終的全球控制實現(xiàn)。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)）。 結(jié)果在沒有超越傳統(tǒng)的控因此，在評估的精確在這篇論文中我們提出一個機電系統(tǒng)中分散震動控制器的設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。另外一個重要的論點限定了SMC的實際應用性就是創(chuàng)新的控制定律導致上面的不確定因素的范圍。這是一個眾所周知的難題并且廣泛的在文獻中經(jīng)過處理。 然