There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The aim of this paper is to present a review of current control techniques for three-phase voltage-source pulsewidth modulated converters. Various techniques, different in concept, have been described in two main groups: linear and nonlinear. The first includes proportional integral (stationary and synchronous) and state feedback controllers, and predictive techniques with constant switching frequency. The second comprises bang-bang (hysteresis, delta modulation) controllers and predictive controllers with on-line optimization. New trends in current control-neural networks and fuzzy-logic-based controllers-are discussed, as well. Selected oscillograms accompany the presentation in order to illustrate properties of the described controller groups.

Current control techniques for three-phase voltage-source PWM converters: a survey

Artificial intelligence (AI) tools, such as expert systems, fuzzy logic, and neural networks are expected to usher a new era in power electronics and motion control in the coming decades. Although these technologies have advanced significantly and have found wide applications, they have hardly touched the power electronics and machine drives area. The paper describes these AI tools and their application in the area of power electronics and motion control. The body of the paper is subdivided into three sections which describe, respectively, the principles and applications of expert systems, fuzzy logic, and neural networks. The theoretical portion of each topic is of direct relevance to the application of power electronics. The example applications in the paper are taken from the published literature. >

Expert system, fuzzy logic, and neural network applications in power electronics and motion control

An online parameter identification method and sensorless control using identified parameters were realized in surface and interior permanent-magnet synchronous motors (SPMSMs and IPMSMs, respectively). As this method does not use rotor position or velocity to identify motor parameters, the identified parameters are not affected by position estimation error under sensorless control. The proposed method can be applied to all kinds of synchronous motors. The effectiveness of the proposed method was verified by experiments in both SPMSMs and IPMSMs.

Sensorless control of permanent-magnet synchronous motors using online parameter identification based on system identification theory

This paper presents a novel speed control scheme of an induction motor (IM) using fuzzy logic control. The fuzzy logic controller (FLC) is based on the indirect vector control. The fuzzy logic speed controller is employed in the outer loop. The complete vector control scheme of the IM drive incorporating the FLC is experimentally implemented using a digital signal processor board DS-1102 for the laboratory 1 hp squirrel cage induction motor. The performances of the proposed FLC based IM drive are investigated and compared to those obtained from the conventional proportional integral (PI) controller based drive both theoretically and experimentally at different dynamic operating conditions such as sudden change in command speed, step change in load, etc. The comparative experimental results show that the FLC is more robust and hence found to be a suitable replacement of the conventional PI controller for the high performance industrial drive applications.

Performances of novel fuzzy logic based indirect vector control for induction motor drive

A description is presented of the fuzzy proportional-plus-integral controller for the vector control system of an induction motor, and the performance of the system using this controller is discussed. The theoretical process of the fuzzy inference and the guide to a design of the controller are presented. This controller is applied to the laboratory model drive system with 0.75 kW induction motor. The simulation results demonstrate the good performance of this system. >

Vector control of induction motor with fuzzy PI controller

There is a growing interest in an electric vehicle (EV), a hybrid-electric vehicle and a fuel-cell vehicle due to air pollution and exhaustion of fossil fuels. These vehicles use motors to obtain the driving force. Switched reluctance motors (SRMs) have a simple structure, high reliability and low cost. Furthermore, these are desirable features for electric vehicle. Our purpose is conversion of a gasoline-powered vehicle to the electric vehicle. This paper presents characteristics of 40 kW switched reluctance motor for EV. Driving force characteristics of EV used SRM are calculated from the torque vs. speed characteristic, and calculation results show good performances for EV. Accelerating performances of EV are also simulated and those results show that the vehicle can drive at the appropriate acceleration.

Driving force characteristics of 40kW switched reluctance motor for electric vehicle

A simplified current control method which enables an inverter to generate 20 kinds of space voltage vectors is developed, and a digital signal processing (DSP) based software field oriented induction motor drive system using this method is also presented. In this system, a particular sampling technique is used to shorten the dead time in the current control system. Furthermore, a current prediction technique is adopted to force the dead time to equal zero theoretically. The test results of the laboratory model drive system verify the validity of this simplified current control method. >

A new simplified current control method for field-oriented induction motor drives

This paper describes an estimation method of the rotor position for switched reluctance motor (SRM) based on the phase inductances. At standstill, the initial rotor position can be obtained by using the phase inductance vectors of all phases. At starting of the SRM, the initial phase excited is determined based on the profiles of the phase inductance in order to move the rotor toward the desired direction. The experimental results show that the rotor position can successfully be estimated by the proposed method.

Estimation of Rotor Position for Switched Reluctance Motor at Standstill

This paper presents the experimental test results of the independent vector control characteristics of two three- phase induction motors (IMs) and two three-phase permanent magnet synchronous motors (PMSMs) fed by a five-leg inverter (FLI). To drive two motors (IMs or PMSMs) independently, the system connected one motor to one three-phase voltage source inverter (three-VSI) is generally used and is required two three- VSIs. Therefore, twelve and ten-switching devices are necessary in the three-VSIs and FLI respectively. Finally, the FLI can decrease two-switches and will be expected for saving space and reduction of inverter losses. Experimental results are verified for the independent driving characteristics in two motors with the FLI.

Ichiro Miki

Papers

Vector control of induction motor with fuzzy PI controller

Driving force characteristics of 40kW switched reluctance motor for electric vehicle

A new simplified current control method for field-oriented induction motor drives

Estimation of Rotor Position for Switched Reluctance Motor at Standstill

Characteristic of independent two AC motor drives fed by a five-leg inverter