The series “Studies in Fuzziness and Soft Computing” contains publications on various topics in the area of soft computing, which include fuzzy sets, rough sets, neural networks, evolutionary computation, probabilistic and evidential reasoning, multi-valued logic, and related fields. The publications within “Studies in Fuzziness and Soft Computing” are primarily monographs and edited volumes. They cover significant recent developments in the field, both of a foundational and applicable character. An important feature of the series is its short publication time and world-wide distribution. This permits a rapid and broad dissemination of research results.
This book presents fuzzy logic and LabVIEW FGPA for designing fuzzy logic controllers. This is a book for implementing fuzzy logic controllers in LabVIEW FPGAs.Despite the FPGA’s attractive features, their adoption by industrial control and signal processing engineers has been slower than processors and DSPs. This is due to several factors. First, these engineers traditionally programmed processors and DSPs using higher level languages, such as C. However, FPGAs possessed complex development tool chains that required designs to be specified using hardware description level (HDL) and register transfer level (RTL) semantics. Furthermore, traditional FPGA development tools lacked intellectual property (IP) blocks for common industrial applications, such as ADC and encoder interface logic, PWM and commutation logic, timing and triggering functions, PID control algorithms, memory management, and data transfer functions. In addition, FPGAs natively supported integer data types only which significantly increased development complexity for analog control and signal processing applications that required math, control, and digital signal processing algorithms, as opposed to floating point processors. Also, traditional FPGA simulation tools were operated at the digital design level and were not interoperable with the type of dynamic simulation tools used by control systems and signal processing engineers for modeling continuous time dynamic system response. Moreover, FPGAs compilation times were relatively long, as compared to processors and DSPs. For example, typical FPGA compilation times today range from 15 to 90 min, whereas processor and DSP compilations are typically completed in less than one minute. Finally, the sequential text-based semantics of traditional register level development tools made it relatively difficult to specify timing and concurrency among parallel processing tasks in a way that leverages the inherent parallel processing capability of FPGA devices.
Contents
+ Chapter 1: Literature Review for Digital Implementations of Fuzzy Logic Type-1 and Type-2
+ Chapter 2: LabVIEW™ FPGA
+ Chapter 3: Real-Time Fuzzy Logic Controllers
+ Chapter 4: Fuzzy Logic Type 1 and Type 2 LabVIEW FPGA Toolkit
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