Min-Max Predictive Control of a Five-Phase Induction Machine

In this paper, a fuzzy-logic based operator is used instead of a traditional cost function for the predictive stator current control of a five-phase induction machine (IM). The min-max operator is explored for the first time as an alternative to the traditional loss function. With this proposal, the selection of voltage vectors does not need weighting factors that are normally used within the loss function and require a cumbersome procedure to tune. In order to cope with conflicting criteria, the proposal uses a decision function that compares predicted errors in the torque producing subspace and in the x-y subspace. Simulations and experimental results are provided, showing how the proposal compares with the traditional method of fixed tuning for predictive stator current control.Ministerio de Economía y Competitividad DPI 2016-76493-C3-1-R y 2014/425Unión Europea DPI 2016-76493-C3-1-R y 2014/425Universidad de Sevilla DPI 2016-76493-C3-1-R y 2014/42

Fuzzy Logic Controller for PMSM

Dual motor drives designs are attractive for high power application because of their mechanical simplicity, traction and regenerative braking control on low friction surfaces. However, such configurations normally require two power inverters with coordinated control. The high cost and large size of packaging needs of the inverters make such dual inverter, dual motor drive configurations are economically less competitive. Therefore, the need for dual motor drives fed by single inverter rising consequently to reduce sizes and costs with respect to the single motor drives, either in industrial or in traction application. This paper aims to investigate the behavior of dual motor drives fed by single inverter using averaging technique MATLAB/Simulink has been chosen as the simulation tools

Evolution of Controllers for the Speed Control in Thyristor Fed Induction Motor Drive

Induction Motors (IMs) are now becoming the pillar of almost all the motoring applications related to the industry and household. The practical applications of IMs usually require constant motoring speed. As a result, different types of control systems for IM's speed controlling have been shaped. One of the important techniques is the utilization of thyristor fed drive. Although, the thyristor fed induction motor drive (TFIMD) offers stable speed performance, the practical speed control demand is much more precise. Hence, this drive system utilizes additional controllers to attain precise speed for practical applications. This paper offers a detailed review of the controllers utilized with the thyristor fed IM drive in the past few decades to achieve good speed control performance. The clear intent of the paper is to provide a comprehensible frame of the pros and cons of the existing controllers developed for the TFIMD speed control requirements. Keywords: Thyristor Fed Drives, Induction Motors, Speed Controller, Conventional Controllers, and Soft Computing Techniques

Improved field oriented control for stand alone dual star induction generator used in wind energy conversion

This paper presents a novel direct rotor flux oriented control with online estimation of magnetizing current and magnetizing inductance applied to self-excited dual star induction generator equipping a wind turbine in remote sites. The induction generator is connected to nonlinear load through two PWM rectifiers. The fuzzy logic controller is used to ensure the DC bus voltage a constant value when changes in speed and load conditions. In this study, a performance comparison between the conventional approach and the novel approach is made. The proposed control strategy is validated by simulation in Matlab/Simulink

Fuzzy Logic Based Direct Power Control of Induction Motor Drive

This paper is the design of an induction motor drive system that can be controlled using direct power control. First the possibilities of direct power control (DPC) of induction motors (IMs) fed by a voltage source inverter have been studied. Principles of this method have been separately evaluated. Also the drive system is more versatile due to its small size and low cost. Therefore it is advantageous to use the system where the speed is estimated by means of a control algorithm instead of measuring. This paper proposed one novel induction motor speed control system with fuzzy logic. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Speed Control of Parallel Connected DSIM Fed by Six Phase Inverter with IFOC Strategy Using ANFIS

This paper describe the presentation of an IM for high load and high-power applications, this kind of applications the motor have a complex coupling between the field and torque. This can be achieve with assist of Indirect Field Oriented Control (IFOC) and parallel connection of two motors. The benefit is that parallel connection can provide the decoupled control of flux and torque for each motor and their concert in different operating environments. The Speed control of two Double Star Induction Motors working in parallel configuration with IFOC using a Fuzzy Logic Controller (FLC) and Adaptive Neuro Fuzzy Inference (ANFIS) controller is investigate in different operating environments. The two motors are connected in parallel at the output of a single six-phase PWM based inverter fed from a DC source. Performance of the projected method under load disturbances is studied through simulation using a MATLAB and evaluation of speed response of two controllers is analyzed. &nbsp

Fuzzy Logic Based Direct Power Control of Induction Motor Drive

This paper is the design of an induction motor drive system that can be controlled using direct power control. First the possibilities of direct power control (DPC) of induction motors (IMs) fed by a voltage source inverter have been studied. Principles of this method have been separately evaluated. Also the drive system is more versatile due to its small size and low cost. Therefore it is advantageous to use the system where the speed is estimated by means of a control algorithm instead of measuring. This paper proposed one novel induction motor speed control system with fuzzy logic. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator

Direct space vector modulation for matrix converter fed dual star induction machine and neuro-fuzzy speed controller

This paper presents the modeling, design, and simulation of an adaptive neuro fuzzy inference strategy (ANFIS) for controlling the speed of the Double Star induction Machine (DSIM), the machine is fed by three phase direct matrix converter which makes directly AC-AC power conversion is modeled using Direct Space Vector Modulation technique(DSVM)  for direct matrix converter. Double star Induction motor is characterized by highly non-linear, complex and time-varying dynamics and inaccessibility of some of the states and outputs for measurements. Hence it can be considered as a challenging engineering problem in the industrial sector. Various advanced control techniques has been devised by various researchers across the world. Some of them are based on the neuro-fuzzy techniques. The main advantage of designing the ANFIS coordination scheme is to control the speed of the DSIM to increase the dynamic performance, to provide good stabilization. To show the effectiveness of our scheme, the proposed method was simulated on an electrical system composed of a 4.5 kW six-phase induction machine and its power inverter. Digital simulation results demonstrate that the deigned ANFIS speed controller realize a good dynamic of the DSIM, a perfect speed tracking with no overshoot, give better performance and high robustness