From this paper emerges that **the** algorithm proposed by me where **the** **rotor** **speed** is calculated directly by **the** robust adaptive reduced order Gopinath flux observer, proved to be efficient both **in** transient regime and **in** indirect field oriented **control** system with three-phase **induction** **motor**. For a more stable flux observer poles were placed on **the** negative real axis, thus obtaining relative simple calculations **in** real time. Also, **the** coefficient K can **control** **the** correction weight generated by **the** corrector and applied to **the** simulator, from **the** flux observer structure. Thus, for a well chosen coefficient K, **the** simulation results confirmed that **the** initial **estimation** error reduces rapidly and **the** estimated value converges to **the** actual one.

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As illustrated **in** Fig. 1, **the** hardware design is classified into six main stages. Firstly, sound signal is to be changed to an electrical signal. SM58 SHURE **dynamic** microphone is **used** here to produce an electrical signal from **the** sound signal vibration. **The** electrical output signal from this microphone is to be amplified using a sound amplifier with a high slew rate. LM386 (Low Voltage Audio Power Amplifier) was **used** here to give **the** required amplification. **The** amplification circuit is shown **in** Fig. 2. **The** input was applied to **the** LM386 through 10K variable resistor so as to meet **the** operating point **of** **the** internal transistors. Pin.1 was connected to pin.8 through 10µF capacitor to increase **the** gain to **the** maximum .pin.7 was connected to **the** ground through 220 µF as a bypass capacitor to bypass unwanted signals to **the** ground. After amplification **the** signal was converted to DC using four diodes as a full wave rectifier as shown **in** Fig. 3. **In** order to overcome **the** problem **of** rippling, a parallel combination **of** a capacitor and a resistor was **used**. **The** microcontroller (ATMEGA16) has three functions as shown **in** Fig. 4. **The** Pulse Width Modulation (PWM) that controls **the** rotational **speed** **of** **the** **motor** will be generated from **the** microcontroller.

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on **of** **speed**, which can further improve performance **of** **the** drive. **The** perfor- mance will further improve with increase **in** sampling frequency. But there are some limitations. It has been observed that **the** controller is suited up to speeds **of** ±700 r.p.m. Better design **of** **the** fuzzy controller with different membership functions and tuning **of** PID parameters will improve performance **of** **the** **motor** **control** even for lower speeds. However, presently **the** new **control** **method** has been discussed and further improvement has been kept for future work. **The** pre- sent work highlights capability **of** **the** new **method** for bi-directional **control** **of** **induction** **motor** with reduced rule base. Introduction **of** **the** final state selector helped to reduce **the** rule base to 36 rules as compared to 72 rules for direct tor- que **control**. Thus **the** advantage **of** **the** proposed technique is to improve real ti- me processing. Moreover, it presents a new **control** technique **of** **induction** **motor**.

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very low value **of** **the** 2 nd column **of** **the** matrix R = A A and this means that this problem is ill- T conditioned ( K problem): this results **in** a flat error surface along **the** 2 K direction [26]. 2 Numerical scaling does not help **in** solving this problem. **In** [24] this problem was attacked by devising an **estimation** **method** which considers **the** constraint (8) indirectly and has good tracking capabilities: **in** particular **in** transient conditions all four electrical parameters can be retrieved, since **the** data matrix is full rank, while **in** sinusoidal steady-state only two K -parameters can be computed, since **the** data matrix has rank 2. Consequently only one electrical parameter can be obtained **in** sinusoidal steady-state, **in** particular **the** **rotor** time constant for vector-controlled **induction** **motor** drives and **the** stator resistance for direct-torque controlled **induction** **motor** drives. **In** these works a selection algorithm has been then developed for choosing **the** parameters to be estimated **in** all working conditions.

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Abstract — Direct torque **control** (DTC) is a new **method** **of** **induction** **motor** **control**. **The** key issue **of** **the** DTC is **the** strategy **of** selecting proper stator voltage vectors to force stator flux and developed torque within a prescribed band. Due to **the** nature **of** hysteresis **control** adopted **in** DTC, there is no difference **in** **control** action between a larger torque error and a small one. It is better to divide **the** torque error into different intervals and give different **control** voltages for each **of** them. To deal with this issue a fuzzy controller has been introduced. But, because **the** number **of** rules is too high some problems arise and **the** **speed** **of** fuzzy reasoning will be affected. **In** this paper, a comparison between a new fuzzy direct-torque **control** (DTFC) with space vector modulation (SVM) is made. **The** principle and a tuning procedure **of** **the** fuzzy direct torque **control** scheme are discussed. **The** simulation results, which illustrate **the** performance **of** **the** proposed **control** scheme **in** comparison with **the** fuzzy hysteresis connected **of** DTC scheme are given.

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“Brushless DC **motor**”[1] is **used** to identify **the** combination **of** AC machine, solid state inverter and **rotor** position sensor that results **in** a drive system having a linear torque – **speed** characteristic as **in** an conventional DC machine High efficiency due to reduced losses, low maintenance and low **rotor** inertia **of** **the** BLDC **motor** have increased **the** demand **of** BLDC motors **in** high power servo [4] and robotic applications. **The** invention **of** modern solid state devices like MOSFET, IGBT and high energy have widely enhanced **the** applications **of** BLDC motors **in** variable **speed** drives. **In** this work, a digital controller is developed for this drive which uses minimum number **of** components employing a recently introduced DSP (TMS320F240) by Texas Instruments (TI) for power electronics applications 7 . First **the** **control** scheme **of** **the** drive is analyzed and its simulated results are validated with test results obtained from developed digital controller

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Nevertheless, this approach requires an important computation time, which can be a serious handicap for its implementation **in** real time. However, since **the** frequency signature **of** a fault is located on a known frequency band [15], then **the** proposed solution **in** this paper consists **of** **the** decrease **of** **the** computation time and **the** **used** memory space by applying **the** processing only on **the** frequency band where **the** signature **of** **the** fault is likely to appear. To highlight **the** contribution merits **of** this new approach **in** **the** detection and **the** monitoring **of** **rotor** faults severity, several experimental tests are conducted on an **induction** **motor** by analysing **the** stator current signal **in** **the** steady-state and without varying **the** load or **speed** **of** **the** **motor**.

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Abstract: Two structures **of** **speed** estimator for AC drive system are developed **in** this paper. **The** mathematical models and **the** simulation results, via numerical simulation, are presented. **The** utility **of** **the** estimator is important for **the** **speed** **control** or for **the** advanced **control** synthesis such as optimal vector **control** **of** **induction** **motor** drives. Besides **of** **speed** **estimation** objective, **the** proposed **method** increases **the** robustness **of** estimators to measurement signal noises.

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Direct current (DC) motors have been widely **used** **in** many industrial applications such as electric vehicles, steel rolling mills, electric cranes, and robotic manipulators due to precise, wide, simple, and continuous **control** characteristics. Traditionally rheostatic armature **control** **method** was widely **used** for **the** **speed** **control** **of** low power dc motors. However **the** controllability, cheapness, higher efficiency, and higher current carrying capabilities **of** static power converters brought a major change **in** **the** performance **of** electrical drives. **The** desired torque-**speed** characteristics could be achieved by **the** use **of** conventional proportional- integral-derivative (PID) controllers. As PID controllers require exact mathematical modeling, **the** performance **of** **the** system is questionable if there is parameter variation. **In** recent years neural network controllers (NNC) were effectively introduced to improve **the** performance **of** nonlinear systems. **The** application **of** NNC is very promising **in** system identification and **control** due to learning ability, massive parallelism, fast adaptation, inherent approximation capability, and high degree **of** tolerance.

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Fig. 15 depicts **the** starting current during **the** first 75ms since **the** machine starts. It's obvious that **the** machine under sensorless mode takes a rather long time to accelerate until **the** ZCP signal is caught for **the** purpose **of** stability. Before **the** commutation moment, **the** current rises slowly **in** lad- der-like shape under a lower voltage on account **of** **the** limit **of** sampling precision. After catching **the** ZCP signal, **the** current surges to its peak and **the** **motor** starts a high-**speed** BEMF-based commutation mode.

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This paper proposed a advance **control** theory applied with an ANN model on a **induction** **motor**. **The** proposed scheme requires **the** information **of** **the** **motor** load torque and **speed** and generate **the** optimum value **of** voltage and frequency. **The** ANN model is configured and trained with some input output pattern. **The** ANN model is **used** is a two layer feed forward network, first layer is a tan-sigmoidal layer and have 8 neurons and another is **of** linear neuron. Computer matlab program is developed to generate **the** required pattern for training. **The** trained network was validated by simulation using Matlab/Simulink. **In** **the** simulation **of** **induction** **motor** drive indirect vector **control** strategy is **used**. **The** proposed technique is easily implemented on **induction** **motor**. **The** validity **of** **the** proposed **control** technique has been established both **in** simulation and experiment at different operating conditions. There is a close agreement between simulation and experimental results and shows **the** **dynamic** behavior **of** **the** system.

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where **the** parameters **of** **the** equivalent circuit are evalu- ated from **the** experimental DC, locked **rotor**, and no-load tests [19]. An optical incremental encoder (SUMTAK Corpo- ration, type LDA-001-1000 CE, 1024 pulses per revolution) is coupled to SPIM shaft **in** order to measure **the** rotational **speed** and compare it to its estimative. A magnetic powder brake Magtrol emulates **the** mechanical load. **The** SPIM windings are fed by two quadrature AC voltages with con- stant V/f ratio generated by an IGBT-based three-leg voltage source inverter (VSI) whose electrical characteristics are summarized **in** Table 2. **The** use **of** a three-leg inverter pre- sents many advantages over a two-leg topology such as gener- ate a zero voltage vector, avoid **the** circulation **of** an AC cur- rent **in** **the** DC link capacitor, and improve **the** output voltage quality **in** terms **of** harmonic distortion [6, 7, 12, 13]. **The** **in**- tegrated sensors to VSI are **used** to measure **the** currents **of**

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1. INTRODUCTION **In** **the** period prior to 2003 Polytechnics **in** Zimbabwe had a mix **of** Information Communication Technologies (ICTs), varying from one institution to **the** other. There was no uniformity as to what ICTs individual institutions invested **in**, so while some institutions had several computer laboratories **of** clone desktops, some did not have even a single lab. While some had connected to **the** internet through **the** dialup system which came through telephone lines, some had no idea what internet was.A breakthrough came **in** 2003 when a non- governmental organization called VVOB, a Belgian abbreviation which translates **in** English to Flemish for Technical Assistance, came **in** with a project called **the** College Information Technology Enhancement Programme (CITEP), which helped to finance, train personnel and equip polytechnics with standard computer and network infrastructure (VVOB project document, 2003). They conducted training workshops for personnel, procured standard desktops, and installed fibre internet connectivity and setup Ethernet networks **in** these institutions. This project became **the** basis for mobile computing **in** Polytechnics. When **the** project ended **in** 2008, **the** institutions were now coordinated and some managed to go a step further by installing wireless access points within institutions using **the** fibre backbone. This allowed staff and students who had WIFI enabled devices to be able to access internet and research

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