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This paper presents the analyses and design of Neural Network (NN) control of a single phase voltage source inverter with an L-C filter using only voltage sensor. A multiple feedback loop PI (Proportional-Integral) controller for PWM (pulse width modulation) inverter is built by root-locus method then simulated using Matlab (Simulink). The proposed NN is traind off-line using the patterns obtained from the simulated inverter with multiple loop PI (Proportional-Integral) controllers. Simulation results show that the proposed NN control can achieve low total harmonic distortion under linear loading condition, small steady state error and good dynamic response under any disturbance change in load. A hardware single phase inverter with programmed pulse width modulation control based on microcontroller is built and implemented with resistive load. حٍثصعنا حكثشنا واذخرسات هٍهع شطٍسي سىطنا يدادأ شٍغي مٍثًذو مٍهذذ الله ذثع ذًدأ سىصُي عتوص ىٌشكنا ذثع مصىًنا / حٍُقرنا حٍهكنأ صهخرسًنا ًييف حٍثييصعنا حكثييشنا واذخرييسات لييقف حييٍرنىف سييسذري ور جساذيينا مييهغي شطٍييسي م ىًٍييصذو مييٍهذذ لييذثنا ازييه حٍعاُطصلاا (ANN) (سىطنا يدادا شٍغًن (single phase inverter يىعيس ًيثد خششيو حٍرنىف سذصي ور (L-C) . جساذيينا دودضيي شطٍييسي (PI controller) واذخرييسات ًييُت حيي ثُنا ضشييع ًٍٍيي ذ شييٍغًن (لا Root locus ً ىييدو ) يايَشت واذخرسات MATLAB (SIMULINK) لايصذلاا ىيطقي ىيَ ٍي ةٌسذيذ حيدشرقًنا حٍثيصعنا حكثيشنا ديتسد , ( off line دودضيًنا شطٍيسًنا عي حي ثُنا ضشيع ًٍٍي ذ شيٍغي جا اذي ٍي اهٍهع لىصذنا ىذ ةٌسذذ خاٍُع واذخرسات ) ( جساذنا (PI controller ٍُت جا اذًنا ئارَ . ايطط حثيسَ ,اذج حهٍهق خاهىشذ ىطعأ حشرقًنا حٍثصعنا حكثشنا شطٍسي ٌأ د ىيذ حٍثيصعنا حكثيشنا ئارَ ٍي مقذرهن .مًذنا شٍغٌ باشطضا يأ دذذ جذٍج حٍكٍياٌُد حتاجرساو جشقرسًنا حناذنا ًف مٍهق (مٍقد شطٍسي ىهع ًُثي يشثًنا حيثُنا ضشع ًٍٍيذ واذخرسات اٌشثرخي شٍغي صاهج مٍثًذ microcontroller .) Received: 3 – 3 2010 Accepted: 2 – 2 2012 Al-Rafidain Engineering Vol.20 No. 6 December 2012 2 1-INTRODUCTION With the increasing demands for high-quality power sources, a pulse-width modulated PWM inverter has been used as a key element for a high performance power conversion system such as uninterruptible power supplies (UPS), medical equipment and communication systems [1]. In the UPS inverter the output voltage is required to be sinusoidal with minimum total harmonic distortion (THD). This is usually achieved by employing a combination of pulse width modulation (PWM) scheme and a second order filter at the output of the inverter .One way of achieving a “clean” sinusoidal load voltage is by using sinusoidal pulse width modulation (SPWM). In this technique the load voltage waveform is compared with a reference sinusoidal voltage waveform and the difference in amplitude is used to control the modulated signal in the control circuit of the power inverter [1]. A multiple loop feedback control scheme can be utilized to achieve good dynamic response and low total harmonic distortion (THD). Although the performance of these schemes are good, the complicated algorithms and the heavy computational demands make the implementations difficult. In recent years, artificial neural networks (ANNs) have received considerable attention and their applications are now being actively explored. ANNs are computing architectures that consist of massively parallel interconnections of simple neural processor. They have the ability to approximate an arbitrary nonlinear mapping and can achieve a higher degree of fault tolerance [2]. When an NN is used in a system control, the NN can be trained either online or off-line. The most popular training algorithm for a feed forward NN is back propagation. It is attractive because it is stable, robust, and efficient [2]. In this paper, first a multiple feedback loop PI controller with inner capacitor current loop and outer voltage loop for PWM inverter is built and simulated using Matlab (Simulink) to obtain adequate example patterns. Then a selected NN with using only voltage sensor is trained off-line with data base comprising all example patterns using matlab programme. When the training is complete this ANN is used to control the inverter on-line. Simulation results show that the proposed ANNs controlled inverter achieve low THD, small steady state error and good dynamic responses under disturbance change in load or input voltage. Finally a simple hardware inverter with programmed PWM based on microcontroller is built. 2-SINGLE PHASE DC-AC PWM INVERTER As shown in Fig. (1), the inverter consists of two legs (A, B) which supplies a singlephase AC output voltage V out to the load. A certain switching algorithm is applied to each of the four switch modules T 1 , T 2 , T 3 , and T 4 in order to control the inverter to generate the desired sinusoidal output with the desired frequency and magnitude. In this paper the unipolar SPWM technique is used to drive the inverter because it gives low THD and decreases the power switches losses. Comparing a control signal V control1 with the carrier signal results a logic signal to control the switches in leg A, and comparing of V control2 with the carrier signal results in logic signal to control the switches in leg B Fig. (2) [3] [4] . Al-Rafidain Engineering Vol.20 No. 6 December 2012 3 Fig. (1): Single phase full bridge inverter Fig. (2): Unipolar PWM scheme 3-COMPONENT SELECTION The magnitude of the ripple current and ripple voltage in the output of the inverter is determined by the size of the LC filters. Once the filter size has been chosen, the PI compensator constants are chosen.. The design specifications for the proposed inverter circuit is shown in table (1) 4-OUTPUT LC FILTER DESIGN A proper design of the LC filter results in a great reduction of the inverter output harmonics and hence provides a very clean power to the load. The inductor ripple current is depend on the size of the inductor and switching frequency. Fig.(3) shows the ripple waveform of the inductor current. The value of the inductance of the output filter inductor is given by [5]:

Analysis and Simulation of Single Phase Inverter Controlled By Neural Network