Design and Implementation of a Fast Digital Fuzzy Logic Controller Using FPGA Technology

Deliparaschos, Kyriakos M.; Nenedakis, F.I.; Tzafestas, Spyros G.

doi:10.1007/s10846-005-9016-2

Cited by 61 publications

(24 citation statements)

References 10 publications

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“…It is observed that the proposed MtFIP offers good flexibility with more I/O capability and better fuzzy rules coverage. The inference speed of the MtFIP is still comparable with that of high inference performance fuzzy processors reported in [11], [19], [20], [5], [21], [22].…”

Section: Mtfip Prototyping and Analysismentioning

confidence: 54%

Multi-tasking of fuzzy inference processor through real-time context switching

Cao

Song

Shi

et al. 2009

2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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Section: Mtfip Prototyping and Analysismentioning

confidence: 54%

Multi-tasking of fuzzy inference processor through real-time context switching

Cao

Song

Shi

et al. 2009

2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics

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“…FLC consists of four subsystems namely, fuzzifier, rulebase or knowledge base, inference engine and defuzzifier [2]- [4]. A fuzzifier adopts fuzzification schemes and protocols of fuzzification operator, which comprises discretization of referential (universe of discourse) , fuzzy partitioning of input and output spaces and selection of the membership grading for various fuzzy sets.…”

Section: A Type I Mamdani Flcmentioning

confidence: 99%

Implementation of FPGA based fuzzy PI approximate control for automatic cruise control system

Maji

Patra

Mahapatra

2014

International Conference on Circuits, Communication, Control and Computing

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in and kkm@nitrkl.ac.in.Abstract-Fuzzy logic systems are widely used in literature for heuristic knowledge based system operation. However most of these systems operate on multiple input to provide a single output. In this paper we have introduced a scheme for implementation of single input single output (SISO) fuzzy logic approximation of PI controller to control a two input single output (TISO) system. In most systems controlled by PI or PID controllers, there exists to input variable namely error (e) and change in error (Δ e) . However, there exists an opportunity to view these controllers as SISO system as Δ e = f (e), hence it is eventually resource effective to approximate these controllers using single input fuzzy variable. This paper introduces this concept and implements it on a model of Automatic Cruise Control (ACC) in an inclined plane with effect of multiple disturbance forces.

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“…However, the authors did not present a power analysis for the predictor itself. The authors in [5] presented a fuzzy logic controller running on an FPGA. This controller used a similar technique like [15] and [14] to forecast data points.…”

Section: Related Workmentioning

confidence: 99%

A generic implementation of a quantified predictor on FPGAs

Thomas

Elhossini

Juurlink

2014

Proceedings of the 24th Edition of the Great Lakes Symposium on VLSI

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Predictors are used in many fields of computer architectures to enhance performance. With good estimations of future system behavior, policies can be developed to improve system performance or reduce power consumption. These policies become more effective if the predictors are implemented in hardware and can provide quantified forecasts and not only binary ones.In this paper, we present and evaluate a generic predictor implemented in VHDL running on an FPGA which produces quantified forecasts. Moreover, a complete scalability analysis is presented which shows that our implementation has a maximum device utilization of less than 5%. Furthermore, we analyze the power consumption of the predictor running on an FPGA. Additionally, we show that this implementation can be clocked by over 210 MHz. Finally, we evaluate a power-saving policy based on our hardware predictor. Based on predicted idle periods, this power-saving policy uses power-saving modes and is able to reduce memory power consumption by 14.3%.

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Design and Implementation of a Fast Digital Fuzzy Logic Controller Using FPGA Technology

Cited by 61 publications

References 10 publications

Multi-tasking of fuzzy inference processor through real-time context switching

Multi-tasking of fuzzy inference processor through real-time context switching

Implementation of FPGA based fuzzy PI approximate control for automatic cruise control system

A generic implementation of a quantified predictor on FPGAs

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