High-performance induction motor (IM) drives require fast dynamic responses, robust to parameter variations, withstand load disturbance, stable control systems, and support easy hardware/software implementation. Fuzzy logic control (FLC) for speed controllers is garnering attention from researchers, since it is proven to produce better results compared with the conventional PI speed controllers. However, fixed parameter FLC experiences performance degradation when the system operates away from the design point or is affected by parameter variations or load disturbances. The purpose of this paper is to design and implement a simple self-tuning fuzzy logic controller (ST-FLC) for IM drives application. The proposed self-tuning mechanism is able to adjust the output scaling factor of the main FLC speed controller by improving the accuracy of the crisp output. The IM drive employed an indirect field-oriented control (IFOC) method fed by a hysteresis current controller (HCC). The fixed parameter FLC for the main speed controller comprises nine rules that are tuned to achieve the best performance. Then, a simple self-tuning mechanism is applied to the main fuzzy logic speed controller. All simulation work was done using Simulink and fuzzy tools in the MATLAB software. The effectiveness of the proposed controller was investigated by conducting a comparative analysis between fixed parameter FLC and ST-FLC in forward and reverse speed operations, with and without load disturbances. Finally, the experimental testing was carried out to validate the simulation results with the aid of a digital signal controller board, dSPACE DS1104, with an induction motor drive system. Based on the results, the ST-FLC showed superior performance in transient and steady-state conditions in terms of various performance measures, such as overshoot, rise time, settling time, and recovery time.

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<span>Fuzzy logic controller has been the main focus for many researchers and industries in motor drives. The popularity of Fuzzy Logic Controller (FLC) is due to its reliability and ability to handle parameters changes during load or disturbance. Fuzzy logic design can be visualized in two categories, mamdani design or Takagi-Sugeno (TS). Mamdani type can facilitate the design process, however it require high computational burden especially with big number of rules and experimental testing. This paper, develop Self-Tuning (ST) mechanism based on Takagi-Sugeno (TS) fuzzy type. The mechanism tunes the input scaling factor of speed fuzzy control of Induction Motor (IM) drives Based on the speed error and changes of error. A comparison study is done between the standard TS and the ST-TS based on simulations approaches considering different speed operations. Speed response characteristics such as rise time, overshoot, and settling time are compared for ST-TS and TS. It was shown that ST-TS has optimum results compared to the standard TS. The significance of the proposed method is that, optimum computational burden reduction is achieved.</span>

In this paper a buck-boost dc-dc converter for pv application is proposed, which is mainly composed of a buck – boost converter, PV panel, load and a battery. Existing dc-dc converter can convert the power from the PV panel, but unfortunately the PV panel can only provide power when there is a high intensity of light. In order to provide power supply to the load without any interruption, buck-boost dc-dc converter is introduced. The power intermittency issue of PV panel can be overcome with the aid of a secondary supply which is in this case, the batter. The integration system between the primary and the secondary supply is controlled by a simple proposed control scheme. Battery act as a power in the low voltage side while PV panel is taking over in the high voltage side. Buck-boost converter is operated either is buck or boost mode according to the performance of the PV panel. This paper is presented the simple control scheme to decide the mode suitable for the buck and boost mode. Various conditions are simulated to verify the working operation of the buck-boost converter and to representing solar panel in real life. Simulation and experimental are carried out to verify the system.

<p>Nowadays, the elimination of the speed sensor in Permanent Magnet Synchronous Machine (PMSM) is greatly recommended to increase efficiency and reduce the cost of the drives. This paper proposes a simple estimator for speed and rotor position of PMSM drives using adaptive controller. The novelties of the proposed method are the simple estimator equations and the absence of the voltage probe which depend on direct and quadrature reference current only. The simplified mathematical model of the PMSM is formulated by using <em>V-I</em> model, based on adaptive control. Then, the speed estimation error of the voltage and current model based are analyzed. Thus, an adaptation mechanism model is established to cancel the error of the measured and estimated <em>d-q</em> currents. Since the output of the estimator is the position feedback, the performances of speed responses are presented. The hardware implementation of proposed sensorless drives is realized via dSPACE DS11103 panel. dSPACE Real Time Implementation (RTI) is the linkage between software and hardware set-up. It automatically processes the MATLAB Simulink model into dSPACE DS11103 processor. The experimental-hardware results demonstrate that the speed and position estimator of the proposed method is able to control the PMSM drives for forward and reverse of speed command, acceleration, deceleration and robustness to load disturbance.</p>

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