Position Sensorless Implementation for a Linear Switched Reluctance Machine

The development of an add-on sensorless position estimator for a 4.8 m Linear Switched Reluctance Machine (LSRM) with minimal modifications to the transducer-based controller is investigated for the first time in this study. LSRMs require position feedback for closed-loop control but present a low cost, high energy efficiency alternative for linear actuation due to their rugged construction and single-sided excitation. Mechanical position transducers mounted on the vehicle are expensive and can impact reliability. The use of a sensorless position estimator removes all electronics from the passive vehicle, resulting in considerable reductions in cost, maintenance, and mechanical complexity. This study examines the use of an add-on processor and data acquisition system for sensorless position estimation. An approach exploiting the active phase windings is used to preserve the normal operation of the transducer-based DSP controller with the goal of limiting reductions in high performance features such as force ripple reduction and velocity control [3]. The estimator system is retrofit to the transducer-based DSP controller by mimicking the output of a mechanical position sensor by emulating a Quadrature encoder. The feasibility and design issues for an add-on or retrofit position estimator are investigated. Although sensorless schemes for rotary Switched Reluctance Machines (SRMs) have been studied in detail, the problem of sensorless implementations for LSRMs has not been addressed. Experimental validation of the proposed sensorless estimation scheme is attempted, but closed-loop operation is not achieved successfully due to air gap fluctuations. In depth analysis of the sources and propagation of error is presented.Master of Scienc

Fuzzy logic type 1 and type 2 based on LabVIEW FPGA

This book is a comprehensive introduction to LabVIEW FPGA™, a package allowing the programming of intelligent digital controllers in field programmable gate arrays (FPGAs) using graphical code. It shows how both potential difficulties with understanding and programming in VHDL and the consequent difficulty and slowness of implementation can be sidestepped. The text includes a clear theoretical explanation of fuzzy logic (type 1 and type 2) with case studies that implement the theory and systematically demonstrate the implementation process. It goes on to describe basic and advanced levels of programming LabVIEW FPGA and show how implementation of fuzzy-logic control in FPGAs improves system responses. A complete toolkit for implementing fuzzy controllers in LabVIEW FPGA has been developed with the book so that readers can generate new fuzzy controllers and deploy them immediately. Problems and their solutions allow readers to practice the techniques and to absorb the theoretical ideas as they arise. Fuzzy Logic Type 1 and Type 2 Based on LabVIEW FPGA™, helps students studying embedded control systems to design and program those controllers more efficiently and to understand the benefits of using fuzzy logic in doing so. Researchers working with FPGAs find the text useful as an introduction to LabVIEW and as a tool helping them design embedded systems