The consequences of the finite wordlength on the performance of a digital fuzzy logic controller (FLC) based on Mamdani's inference algorithm are investigated. Digital implementations of FLCs involve three main types of errors due to the finiteness of the wordlength: analog-to-digital errors, membership function errors, and arithmetic errors. First, a statistical evaluation of the consequences of these errors is performed. The effects of the digital resolution on the controller response are discussed. Then, the dynamic behavior of a closed-loop fuzzy system composed of a digitized FLC and a second-order plant is evaluated; a qualitative evaluation of time-domain parameters as a function of the universe discretization is carried out. The results show that, as in the case of conventional control strategies, bias effects and limit cycles are generated as a consequence of the digitization. Although these distortions diminish when the discretization is sufficiently refined, they are very difficult to predict because of the nonlinear nature of both quantization and fuzzy operation. In this sense, the availability of computer-aided design (CAD) tools that permit the specification of the wordlength is essential to validate the design.

Consequences of the digitization on the performance of a fuzzy logic controller

This article describes a pipeline sequential fuzzy controller endowed with great flexibility and high performance. Its design allows for the possibility to implement it on programmable devices at low cost. To optimise the design and performance of the circuit, a number of simplifications over traditional fuzzy algorithms are pointed out. For the manipulation of simplification procedures, some software tools of knowledge acquisition and compilation have been developed. The hardware design is presented at a level of block diagram showing the different components and the solutions adopted in each case. The characteristics of this design make it adequate for working with a great number of input and output variables and with a high number of rules. Under these conditions, the speed of calculation and the circuit dimensions are optimal. It can be used in any field of application where a fuzzy control of high complexity is to be established.

Hardware implementation of a pipeline fuzzy controller and software tools

The necessity for fast fuzzy controllers has caused a tendency to use SIMD hardware architecture, with the handicap of flexibility loss. In this paper we present a pipeline architecture realisation, with intermediate qualities between a microprocessor and a SIMD design. Also, we present several simplifications to fuzzy logic that make possible the pipeline execution of minimum, maximum, and mean of maximum method.

https://ieeexplore.ieee.org/iel3/4864/13530/00622786.pdf

A pipe-line fuzzy controller in FPGA

This study develops a new integrated measurement and control system for intermixed biogas and photovoltaic systems to achieve safe and optimal energy usage. Literature and field studies show that existing control methods on small- to medium-scale systems fall short of comprehensive system optimization and fault diagnosis, hence the need to revisit these control methods. The control strategy developed in this study is intelligent as it is wholly based on fuzzy logic algorithms. Fuzzy logic controllers due to their superior nonlinear problem solving capabilities to classical controllers considerably simplify controller design. The mathematical models that define classical controllers are difficult or impossible to realize in biogas and photovoltaic generation process. A microcontroller centered fuzzy logic measurement and control embedded system is designed and developed on the existing hybrid biogas and photovoltaic installations. The designed system is able to accurately predict digester stability, quantify biogas output, and carry out biogas fault detection and control. Optimized battery charging and photovoltaic fault detection and control are also successfully implemented. The system is able to optimize the operation and performance of biogas and photovoltaic energy generation.

/pdf/fuzzy-logic-system-for-intermixed-biogas-and-photovoltaics-1moc7y1nvw.pdf

Fuzzy Logic System for Intermixed Biogas and Photovoltaics Measurement and Control

The paper presents the ASIC design of a digital fuzzy logic circuit for medical diagnostic applications. The system on chip under consideration uses fuzzifier, memory and defuzzifier for fuzzifying the patient data, storing the membership function values and defuzzifying the membership function values to get the output decision. The proposed circuit uses triangular trapezoidal membership functions for fuzzification patients' data. For minimizing the transistor count, the proposed circuit uses 3T XOR gates and 8T adders for its design. The entire work has been carried out using TSMC 0.35 µm CMOS process. Post layout TSPICE simulation of the whole circuit indicates a delay of 31.27 ns and the average power dissipation of the system on chip is 123.49 mW which indicates a less delay and less power dissipation than the comparable embedded systems reported earlier.

V. Samoladas

Papers

Special-purpose architectures for fuzzy logic controllers