H. Abu-Rub

Quasi-Z-Source Inverter-Based Photovoltaic Generation System With Maximum Power Tracking Control Using ANFIS

The paper proposes an artificial-intelligence-based solution to interface and deliver maximum power from a photovoltaic (PV) power generating system in standalone operation. The interface between the PV dc source and the load is accomplished by a quasi-Z-source inverter (qZSI). The maximum power delivery to the load is ensured by an adaptive neuro-fuzzy inference system (ANFIS) based on maximum power point tracking (MPPT). The proposed ANFIS-based MPPT offers an extremely fast dynamic response with high accuracy. The closed-loop control of the qZSI regulates the shoot through duty ratio and the modulation index to effectively control the injected power and maintain the stringent voltage, current, and frequency conditions. The proposed technique is tested for isolated load conditions. Simulation and experimental approaches are used to validate the proposed scheme.

Artificial-neural-network-based sensorless nonlinear control of induction motors

In this paper, two architectures of artificial neural networks (ANNs) are developed and used to correct the performance of sensorless nonlinear control of induction motor systems. Feedforward multilayer perception, an Elman recurrent ANN, and a two-layer feedforward ANN is used in the control process. The method is based on the use of ANN to get an appropriate correction for improving the estimated speed. Simulation and experimental results were carried out for the proposed control system. An induction motor fed by voltage source inverter was used in the experimental system. A digital signal processor and field-programmable gate arrays were used to implement the control algorithm.

Application of Speed and Load Torque Observers in High-Speed Train Drive for Diagnostic Purposes

In this paper, an application of speed and load torque observers is presented. The aim of the observer implementation is to be used in the diagnostic system for a motor speed sensor and a torque transmission system. The diagnostic system is dedicated to the high-speed train propelled by an induction motor. An analysis of the observed variables allows the identification of problems in the mechanical part of the main traction drive. For example, in the case of speed sensor faults, the motor control system could be switched into speed-sensorless control. The proposed observers were verified by simulation and on a test bench for 1.2-MW rail vehicle motor used in high-speed trains.

Generalized Duty-Ratio-Based Pulsewidth Modulation Technique for a Three-to-

This paper presents a novel topology for a direct ac-ac power converter, called as the “three-to- k” phase matrix converter. The input to the proposed matrix converter configuration is a three-phase fixed voltage and a fixed frequency supply from the grid. The output is a variable voltage and variable frequency ac supply of any number of phases (k phase). However, the discussion is limited here for a k that is equal to odd number of phases. As an example, a “three-to-five” phase matrix converter is utilized for discussion and analysis. This paper also proposes two pulsewidth modulation (PWM) control techniques for the general topology of the “three-to- k” phase matrix converter. This is based on the so-called direct duty ratio PWM (DPWM). In one presented technique, the output voltage is limited to one half of the input voltage. For the other proposed scheme, the output voltage is enhanced to 78.86% of the input voltage. The proposed control algorithm is validated using simulation and an experimental approach.

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This paper presents a sensorless control system for induction motors, which is realized on a fixed-point digital signal processor (DSP) and field programmable gate arrays (FPGAs). An observer system has been developed for estimation of speed and the other state variables. The proposed observer system is verified for different conditions of motor operation. Experimental results for the control system fed by voltage source inverter controlled using predictive current controller are presented.

Phase Matrix Converter

This paper presents and analyses the operation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) based maximum power point tracker (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the solar PV modules by changing the duty ratio of the boost converter. The duty ratio of boost converter is calculated for given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate the maximum power corresponding to the given solar irradiance level and temperature. The response of ANFIS based control system is highly precise and offers very fast response. Simulation results are provided to validate the concept.

Speed observer system for advanced sensorless control of induction motor

The first five-phase induction motor drive system was proposed in the late 1970s for adjustable speed drive applications. Since then, a considerable research effort has been in place to develop commercially feasible multiphase drive systems. Since the three-phase supply is available from the grid, there is a need to develop a static phase transformation system to obtain a multiphase supply from the available three-phase supply. Thus, this paper proposes a novel transformer connection scheme to convert the three-phase grid supply to a five-phase fixed voltage and fixed frequency supply. The proposed transformer connection outputs five phases and, thus, can be used in applications requiring a five-phase supply. Currently, the five-phase motor drive is a commercially viable solution. The five-phase transmission system can be investigated further as an efficient solution for bulk power transfer. The connection scheme is elaborated by using the simulation and experimental approach to prove the viability of the implementation. The geometry of the fabricated transformer is elaborated in this paper.

Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module

This paper analyses the operation of an adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking (MPPT) for solar photovoltaic (SPV) energy generation system. The MPPT works on the principle of adjusting the voltage of the SPV modules by changing the duty ratio of the boost converter. The duty ratio of the boost converter is calculated for a given solar irradiance and temperature condition by a closed-loop control scheme. The ANFIS is trained to generate maximum power corresponding to the given solar irradiance level and temperature. The response of the ANFIS-based control system is highly precise and offers an extremely fast response. The response time is seen as nearly 1 ms for fast varying cell temperature and 6 ms for fast varying solar irradiance. The simulation is done for fast-changing solar irradiance and temperature conditions. The response of the proposed controller is also presented.

A Novel Three-Phase to Five-Phase Transformation Using a Special Transformer Connection

An advanced solution for low-cost implementation of the sensorless vector control of an induction motor is presented in this paper. The proposed system is based on a new set of variables for the induction motor model. The system works using vectors coordinates in a stationary /spl alpha/-/spl beta/ frame of references. A phase-locked loop was used to control the angle between the flux vector and the stator current vector. The induction motor model variables and the rotor velocity are calculated from simple equations based on the steady state relationships for the active and reactive powers. A current controller for the current-regulated pulsewidth-modulation inverter based on the simplified load model is presented. The proposed current controller is based on the back-electromotive-force calculation. The developed sensorless system was investigated both in simulations and experiments. The overall system was implemented using a simple and cheap fixed-point microcontroller.

Adaptive neuro-fuzzy inference system-based maximum power point tracking of solar PV modules for fast varying solar radiations

This paper presents a simple and novel sensorless scheme for five-phase induction motor control. The power measurement is used for speed computation. The drive is controlled using direct torque control (DTC). Speed sensorless control scheme is tested under speed variation and load changes. The control method is simulated and implemented in real time on the DS1103 board.