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The weighting factor adjustment limits the extensive application of conventional model predictive torque control in practice. In this paper, a model predictive torque control strategy with gravitat...

The microgrid power plant contains a large number of power electronic converters, which inevitably produce power quality problems such as harmonic noise and voltage fluctuations. Harmonics noise is...

A metering roundabout where traffic is controlled by signals where phase times are influenced by queue detector occupancy may be the solution to reduce queue lengths under unbalanced traffic flows. In the past decades, a number of studies have attempted to evaluate the effectiveness of metering roundabout, especially on the dominant approach. Little studies, however, have been directed on prediction of the queuing lengths, which is essential to determine the detector locations. This paper introduces a queue length estimation model using adaptive neuro fuzzy inference system for unbalanced roundabout traffic flows. The adaptive neuro fuzzy inference system model consists of an input layer representing four parameters as arrival volumes, conflicting volumes, phase green and red time, and output layer with four neuron representing queuing length. MATLAB software and additional statistical tests were used as the tool to develop the models for the data. In order to conduct credible model validations, model output data were compared against the observed data collected using drones. The results from the analysis demonstrated that adaptive neuro fuzzy inference system model is able to estimate the queuing length at metering roundabouts. Thus, it is expected that the adaptive neuro fuzzy inference system model will help practitioners in determining optimal detector locations and will be a foundation research for roundabouts with signals.

In this article, the adaptive neuro-fuzzy inference system (ANFIS) and multiconfiguration gas-turbines are used to predict the optimal gas-turbine operating parameters. The principle formulations of gas-turbine configurations with various operating conditions are introduced in detail. The effects of different parameters have been analyzed to select the optimum gas-turbine configuration. The adopted ANFIS model has five inputs, namely, isentropic turbine efficiency (Teff), isentropic compressor efficiency (Ceff), ambient temperature (T1), pressure ratio (rp), and turbine inlet temperature (TIT), as well as three outputs, fuel consumption, power output, and thermal efficiency. Both actual reported information, from Baiji Gas-Turbines of Iraq, and simulated data were utilized with the ANFIS model. The results show that, at an isentropic compressor efficiency of 100% and turbine inlet temperature of 1900 K, the peak thermal efficiency amounts to 63% and 375 MW of power resulted, which was the peak value of the power output. Furthermore, at an isentropic compressor efficiency of 100% and a pressure ratio of 30, a peak specific fuel consumption amount of 0.033 kg/kWh was obtained. The predicted results reveal that the proposed model determines the operating conditions that strongly influence the performance of the gas-turbine. In addition, the predicted results of the simulated regenerative gas-turbine (RGT) and ANFIS model were satisfactory compared to that of the foregoing Baiji Gas-Turbines.

The growth of using wind energy on a large scale increases the demand for wind energy conversion machines (WECMs), among these converters, the doubly-fed induction generator (DFIG) is the favorite choice. However, DFIG is very sensitive to wind speed variations and grid faults during operation. In order to overcome these undesirable characteristics, this paper proposes a hierarchical fault tolerant control (FTC) to improve the performance of DFIG. The hierarchical fault tolerant control (FTC) approach consists of pitch angle control (PAC) and maximum power point tracking (MPPT). This hierarchical approach demonstrates the robust response under various (low, rated, and high) wind speed ranges and reduces the undesirable DC voltage overshoots during short-circuit disorder. The simulation results are summarized in a logical table, which depicts the order of controlling scheme and operation for a sustainable energy generation system. The proposed control scheme achieved the healthy and the robust dynamic response without deteriorating the grid power quality or stressing the converters, and approved the effectiveness to suppress the DC voltage overshoots and tolerate the lower down short-circuit disorder to its rated range.

Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness. Over the past few years, multiple types of modifications have been proposed onto the Direct Torque Control (DTC) scheme. Among others is the implementation of Space Vector Modulation (SVM). In this paper, two new control strategies are proposed onto an SVM-DTC. Instead of using PI torque and flux controllers, a fuzzy logic control method is implemented in the proposed modification to achieve a more constant switching frequency while minimizing the torque error. The fuzzy logic controller controls the voltages in direct and quadratic reference frame (Vd, Vq). This approach fully utilizes the switching capability of the inverter and thus improving the overall system performance. To overcome issues in open loop stator flux such as DC drift and saturation, a closed loop estimation method of stator flux is also proposed based on voltage model and low pass filter. The performance of the proposed control strategy is benchmarked with that of a conventional DTC–SVM. Simulations and experiments were carried out and the results show that the proposed method outperforms the conventional DTC-SVM in terms of DC-offset elimination and overall system robustness.

Eddy current testing (ECT) is an accurate, widely used and well-understood inspection technique, particularly in the aircraft and nuclear industries. The coating thickness or lift-off will influence the measurement of defect depth on pipes or plates. It will be an uncertain decision condition whether the defects on a workpiece are cracks or scratches. This problem can lead to the occurrence of pipe leakages, besides causing the degradation of a company&rsquo, s productivity and most importantly risking the safety of workers. In this paper, a novel eddy current testing error compensation technique based on Mamdani-type fuzzy coupled differential and absolute probes was proposed. The general descriptions of the proposed ECT technique include details of the system design, intelligent fuzzy logic design and Simulink block development design. The detailed description of the proposed probe selection, design and instrumentation of the error compensation of eddy current testing (ECECT) along with the absolute probe and differential probe relevant to the present research work are presented. The ECECT simulation and hardware design are proposed, using the fuzzy logic technique for the development of the new methodology. The depths of the defect coefficients of the probe&rsquo, s lift-off caused by the coating thickness were measured by using a designed setup. In this result, the ECECT gives an optimum correction for the lift-off, in which the reduction of error is only within 0.1% of its all-out value. Finally, the ECECT is used to measure lift-off in a range of approximately 1 mm to 5 mm, and the performance of the proposed method in non-linear cracks is assessed.

Dynamic inversion (DI) is a controller technique by which existing undesirable dynamics are cancelled out and changed by desirable dynamics. The application of induction motor drives with sinusoidal input currents a matrix converter combined with DI is used which directly connects a three-phase input voltage source to a three-phase (AC-AC converter) without dc-link components. This paper presents a novelty of using nonlinear dynamic inverse controller with matrix converter topologies on three phase induction motor. The efficiency of the converter and their modulation techniques for the implementation of the strategies is increased. The speed response tracking and torque ripple minimization is achieved. The robustness of the proposed method has been confirmed from simulation and experimental model.

The fundamental idea of direct torque control of induction machines is investigated in order to emphasize the property produced by a given voltage vector on stator flux and torque variations. The proposed control system is based on Space Vector Modulation (SVM) of electrical machines, Improvement model reference adaptive system, real time of stator resistance and estimation of stator flux. The purpose of this control is to minimize electromagnetic torque and flux ripple and minimizing distortion of stator current. In this proposed method, PI torque and PI flux controller are designed to achieve estimated torque and flux with good tracking and fast response with reference torque and there is no steady state error. In addition, design of PI torque and PI flux controller are used to optimize voltages in d-q reference frame that applied to SVM. The simulation Results of proposed DTC-SVM have complete excellent performance in steady and transient states as compared with classical DTC-SVM.

Direct torque control based on space vector modulation (SVM-DTC) protects the DTC transient merits. Furthermore, it creates better quality steady-state performance in a wide speed range. The modified method of DTC using SVM improves the electrical magnitudes of asynchronous machines, such as minimizing the stator current distortions, the stator flux with electromagnetic torque without ripple, the fast response of the rotor speed, and the constant switching frequency. In this paper, the proposed method is based on two new control strategies for direct torque control with space vector modulation. First, fuzzy logic control is used instead of the PI torque and a PI flux controller to minimizing the torque error and to achieve a constant switching frequency. The voltages in the direct and quadratic reference frame (V d ,V q ) d q are achieved by fuzzy logic control. In this scheme, the switching capability of the inverter is fully utilized, which improves the system performance. Second, the close loop of stator flux estimation based on the voltage model and a low pass filter is used to counteract the drawbacks in the open loop of the stator flux such as the problems saturation and dc drift. The response of this new control strategy is compared with DTC-SVM. The experimental and simulation results demonstrate that the proposed control topology outperforms the conventional DTC-SVM in terms of system robustness and eliminating the bad outcome of dc-offset.

Various aspects related to controlling induction motor are investigated. Direct torque control is an original high performance control strategy in the field of AC drive. In this proposed method, the control system is based on Space Vector Modulation (SVM), amplitude of voltage in direct- quadrature reference frame (d-q reference) and angle of stator flux. Amplitude of stator voltage is controlled by PI torque and PI flux controller. The stator flux angle is adjusted by rotor angular frequency and slip angular frequency. Then, the reference torque and the estimated torque is applied to the input of PI torque controller and the control quadrature axis voltage is determined. The control d-axis voltage is determined from the flux calculator. These q and d axis voltage are converted into amplitude voltage. By applying polar to Cartesian on amplitude voltage and stator flux angle, direct voltage and quadratures voltage are generated. The reference stator voltages in d-q are calculated based on forcing the stator voltage error to zero at next sampling period. By applying inverse park transformation on d-q voltages, the stator voltages in α and β frame are generated and apply to SVM. From the output of SVM, the motor control signal is generated and the speed of the induction motor regulated toward the rated speed. The simulation Results have demonstrated exceptional performance in steady and transient states and shows that decrease of torque and flux ripples is achieved in a complete speed range.

Load Frequency Control (LFC) is one of power systems important requirements which maintain the zero steady-state errors in the frequency changing and restoring the natural frequency to its normal position. Many problems are subject to LFC such as suddenly large load or suddenly disconnecting generating unit by the protection device. In this paper, multi-area Frequency Control by using the combination of PSO and fuzzy logic control (FLC) technique. PSO optimization method is used to tuning the fuzzy controller input and output gains. Four of an interconnected electrical power system used as a testing the effectiveness of the proposed method compared to a conventional PI controller and scaled-fuzzy controller. The simulation result has been shown that the controller can generate the best dynamic response in multi-load conditions.

One of the most important rules in electric power system operation and control is Load Frequency Controller (LFC). Many problems are subject to LFC such as a generating unit is suddenly disconnected by the protection equipment and suddenly large load is connected or disconnected. The frequency gets deviated from nominal value when the real power balance is harmed due to disturbances.LFC is responsible for load balancing and restoring the natural frequency to its natural position. In this paper, PSO-fuzzy logic technique for Load Frequency Control system was proposed. PSO optimization method is used to tuning the input and output gains for the fuzzy controller. The proposed method has been tested on two symmetrical thermal areas of an interconnected electrical power system. The simulation results are carried out in term of effectiveness of the frequency time response on its damping and compared it to common PID controller. The results show the performances of the proposed controller have quite promising compared to PID controller.

typically, the spacecraft model has high uncertainties and the dynamic inverse inner loop controller alone may not achieve acceptable performance. Therefore, a robust outer loop must be added to compensate this in- ner-loop deficit. In this paper, a robust controller based on dynamic inverse technique for proto type vehicle X-38 model was proposed. The controller contains two loops. The inner loop is dynamic inverse controller which cancels existing system dynamics and replaces them with designer specified response, and the outer loop is a Linear Quadratic Gaussian (LQG) which is used as a robust approach. Several forms of desired dynamic are presented and evaluated in terms of performance and robustness including a proportional dy- namics, proportional integral dynamics, flying quality dynamics and ride quality dynamics. The simulation results shows that flying quality and ride quality have been used as a desired dynamics. The ride quality has been proved to be more robust, then the other desired dynamics, against wide range of system parameter variation.

Recently, there has been a growing demand for flow-temperature sensors for industrial, automotive, domestic and medical applications. A quick response and low power consumption. Hot Wire Mass Airflow Sensors are used in automotive industry to measure the mass air flow intake into the internal combustion engine according to heat transfer principles. As the heat transfer process is sensitive both to the velocity and temperature of the air, any changes in temperature must be compensated for in order to achieve accurate mass flow measurements. In this paper, the development of a Fuzzy Temperature Compensation Scheme (FTCS) for Hot Wire Mass Airflow (MAF) Sensor is presented. This FTCS used to compensate the measurement error occurred by using Sugeno type FIS for temperature of 60iC-100iC. In order to verify the performance of the proposed Hot Wire MAF Sensor temperature compensation scheme, first a simulation model is developed using Matlab/Simulink. Then, the algorithm for FTCS has been developed using Programming C Language and been implemented in hardware based real-time using Digital Signal Controllers, (dsPIC). The effectiveness of the proposed fuzzy compensation scheme is verified with the estimation error within only ±1% over full-scale value.

Matrix converters as induction motor drivers have received considerable attention in recent years because of its good alternative to Voltage Source Inverter Pulse Width Modulation (VSI-PWM) converters. This study focus on developing a mathematical model for a Space Vector Modulated (SVM) direct controlled matrix converter. The mathematical expressions relating the input and output of the three phase matrix converter are implemented by using MATLAB/SIMULINK. The duty cycles of the switches are modeled using space vector modulation for 0.5 and 0.866 voltage transfer ratios. Simulations of the matrix converter loaded by passive RL load and active induction motor are performed. A unique feature of the proposed model is that it requires very less computation time and less memory compared to the power circuit realized by using actual switches. In addition, it offers better spectral performances, full control of the input power factor, fully utilization of input voltages, improve modulation performance and output voltage close to sinusoidal.

Background: Typical steady state studies always treat the peak power demands as the worst case conditions. Periods of light load area also critical in the assessment of the possible state of a power system. While heavy load conditions are generally associated with overload, low voltage and generation deficiency, light load conditions may give rise to over-voltage and undesirable reactive power requirements at generation side. Method: This paper focus on study the effect of DG Optimizing on overload Transmission line Stability. The system dispatch constraints should be taken into account to compensate for varying DG generation output and to enhance the operational performance of power systems. Findings: This dispatching operation depends on the change of DG generation and the dispatching strategy. The impact of DG generation uncertainty is limited with the generation dispatching operation and should not be neglected in system analysis. Application: distributed generators based wind turbine to investigate the effect of DG on Transmission line stability.

Liquid tank systems play important role in industrial application such as in food processing, beverage, dairy, filtration, effluent treatment, pharmaceutical industry, water purification system, industrial chemical processing and spray coating. A typical situation is one that requires fluid to be supplied to a tank at a constant rate which has Two-Input Two-Output (TITO). The accuracy and stability of TITO is one of the key factors of process which have cross coupling between process input and output. Unlike traditional neural network weight adaptation using gradient descent method, Fuzzy Adaptive PID control technique was utilized for adaptive tuning and fine tuning the controller’s parameters. Design approach for controlling liquid levels of Coupled Tank TITO system by using Fuzzy Adaptive PID controllers. Tuning method for parameters of improved Fuzzy Adaptive, Particle Swamp Optimization and Neural network controllers ware also discussed. Experimental results demonstrate that the performances of proposed method perform well compared with convention Fuzzy and Tuned Fuzzy controllers; it was shown that Fuzzy Adaptive controller exhibited better performance in terms of transient response analysis.

The Induction Motors utilizing Matrix Converters with Direct Torque Control (DTC) is a great responsibility for motor control scheme with expeditious torque and flux replications. This paper shwed a new power factor control along with the existing DTC matrix converter induction motor drive. The core benefits of the DTC matrix converter are improved with those of the power factor technique, the required voltage vectors is producing under 0.86 input power factor operations. The implementation of this kind of controller is done by using the TMS320F28335. The results validate the good quality and robustness in the proposed system dynamic response and reduction in the transient motor ripple torque.

In conventional direct torque controlled (DTC) induction motor drive, there is usually undesired torque and flux ripple. The given torque is the speed output regulator; therefore, it necessary continues tuning for adjusting parameters Kp, Ki. In conventional proportional- integral (PI) speed controller, the performance of motor may differ over time that may cause unexpected torque disturbances, causing sluggishness of a control system. Tuning PID parameters are essential to DTC system to improve the performance of the system at a low speeds. In this paper particle swarm optimization (PSO) proposed to correct the parameters (Kp, Ki) of a speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. Firstly, introduce brief description for conventional DTC design and PSO. Secondly, close loop speed controller in DTC for induction motor using PSO technique to provide high performance of accuracy. Finally, simulation results demonstrate that a reduction of torque and flux ripples is achieved in a whole speed range. Key words: Particle swarm optimization, PID controller, direct torque control.

The accuracy and stability of many systems in chemical and process industries which has Two-Input Two-Output (TITO) is one of the key factors of process which have cross coupling between process input and output. Unlike traditional neural network weight adaptation using gradient descent method, Hybrid Genetic-Immune technique was utilized for adaptive tuning of neural network weights adjustment and fine tuning the controller's parameters. The TITO is modeled in Simulink and the Hybrid GA-AIS algorithm is implemented in MATLAB. The performances of proposed method also compared with GA and Artificial Immune System (AIS) alone, it was shown that hybrid PI-NN hybrid GA-AIS have superior features, stable convergence characteristic and good computational efficiency.

Energy efficiency is hot area of research for today researcher. A lot has been done in this regard for managing different types of energy. Management of available resources is one of the basic jobs for researcher for all types of energy. Building energy management that involves efficient equipment system is a hot topic in Malaysian Green technology vision that is costing a lot to the national economy, and its contribution for management is not as it is supposed to be. User comfort, efficient and active control on building energy system is one of the issues needed to be addressed seriously. Following research proposes a smart energy controller system that is specifically designed for campus resources efficient management. The system comprises of wireless control on lighting system that is first focus of the current research.

Recently, the design of RF power amplifiers (PAs) for modern wireless systems are faced with a difficult tradeoff for example, cellphone; battery lifetime is largely determined by the power efficiency of the PA and high spectral efficiency which have ability to transmit data at the highest possible rate for a given channel bandwidth. This paper presents the design a multi stage class AB power Amplifier with high power added efficiency (PAE) and acceptable linearity for the WLAN applications. The open-circuited third harmonic control circuit enhances the efficiency of the PA without deteriorating the linearity of class-AB mode of the PA. The voltage and current waveforms are simulated to evaluate the appropriate operation for the modes. The effectiveness of the proposed controller has been verified by comparing proposed method with another methods using simulation study under a variety of conditions. The proposed circuit operation for a WLAN signals delivers a power-added efficiency (PAE) of 37.6% is measured at 31.6-dBm output power while dissipating 34.61 mA from a 1.8V supply. Finally, the proposed PA is show a good and acceptable result for the WLAN system.

In conventional direct torque controlled (DTC) induction motor drive, there is usually undesired torque and flux ripple. In this paper close loop stator flux estimation of DTC with space vector modulation under heavy load at low speed was proposed. First, brief description of stator currents in direct–quadrature reference frame with voltage model. Second, close loop stator flux feedback used through PID controller to correct the value of stator flux estimation and eliminate error. In addition, low pass filter also used instead of pure integration to avoid saturation problem. Finally, simulation results show that the flux and torque ripples are greatly reduced when compared with open loop of stator flux estimation.

The performance of the neural network based estimator is investigated with simulations for variations in the rotor resistance from their nominal values, with both speed and load torque disturbances.In this paper, adaptive speed control of induction motor using neural network inverse control scheme are proposed. The controller-structure design is based on a vector control scheme that transforms the three phase motor currents into flux and torque generating current components. The experiment results show that the proposed scheme has excellent dynamic and static control performance.