FPGA-Based Fuzzy Logic: Design and Applications – a Review

Sulaiman, Nasri; Obaid, Zeyad Assi; Marhaban, Mohammad Hamiruce; Hamidon, Mohd Nizar

doi:10.7763/ijet.2009.v1.90

Cited by 43 publications

(23 citation statements)

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“…The interconnections consist of electrically programmable switches which is why FPGA differs from custom integrated circuits, as a custom integrated circuit is programmed using the technology to form metal interconnections between logic blocks. In an FPGA, logic blocks are implemented using multiple-level low fan in gates, which gives it a more compact design compared to an implementation with two-level AND-OR logic [27]. Microcontrollers and FPGA's provide functional blocks to build type-1 FLS and type-2 FLS, in which crisp inputs and outputs, and parameters are defined in 8-bits.…”

Section: Fpga and Microcontrollers Used For Fuzzy Logic Applicationsmentioning

confidence: 99%

Literature Review for Digital Implementations of Fuzzy Logic Type-1 and Type-2

Ponce-Cruz

Molina

MacCleery

2015

Fuzzy Logic Type 1 and Type 2 Based on LabVIEW™ FPGA

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Some works are described below where optimization Type-1 and Type-2 FLS have had relative success according to different areas, illustrating the advantages of using methods to automate process with fuzzy controllers.The work of Sudha and Vijai Santhi [1], deals with the load frequency control (LFC) problem, which has been a major subject in electrical power system such as design and operation. In practice, LFC systems use simple proportional integral (PI) controllers. However, it shows that fuzzy logic controller is adaptive in nature and is applied successfully for power system stabilization control. Authors propose a type-2 fuzzy approach for load frequency control of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The performance of the type-2 controller is compared with conventional controller and Type-1 fuzzy controller with regard to Generation Rate Constraint (GRC). The system parametric uncertainties are verified by changing parameters by 40% simultaneously from their typical values.The authors Jammeth and Fleury in their work [2] use an interval Type-2 FLC that gets better video quality compared with traditional controllers. They also use Type-1 FLC to show the response in different network scenarios, such like Internet cross-traffic, video streams occupy on an Internet protocol (IP) network. Type-2 FLC is designed for Internet conditions so they can react successfully to the network conditions of an IP-network. Type-2 FLC resulted in an order of magnitude performance improvement in comparison with Type-1 FLC.The work of Lee and Lin [3], proposes a new control scheme using type-2 fuzzy neural network (type-2 FNN) and adaptive filter for controlling nonlinear uncertain systems. This type-2 FNN model combines the advantages of type-2 fuzzy logic systems and neural networks. The type-2 FNN system has the ability of universal approximation, which identifies nonlinear dynamic systems. The control scheme consists of a PD-type adaptive FNN controller and a pre-filter. The adaptive filter is

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Section: Fpga and Microcontrollers Used For Fuzzy Logic Applicationsmentioning

confidence: 99%

Literature Review for Digital Implementations of Fuzzy Logic Type-1 and Type-2

Ponce-Cruz

Molina

MacCleery

2015

Fuzzy Logic Type 1 and Type 2 Based on LabVIEW™ FPGA

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“…The general inference process usually proceeds in four (or three for a system with only a fuzzy output) steps (Czogała and Pedrycz, 1985;Rutkowska et al, 1997;Sulaiman et al, 2009) …”

Section: Crisp Inputsmentioning

confidence: 99%

Decomposition of the fuzzy inference system for implementation in the FPGA structure

Hrynkiewicz¹

2013

International Journal of Applied Mathematics and Computer Science

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The paper presents the design and implementation of a digital rule-relational fuzzy logic controller. Classical and decomposed logical structures of fuzzy systems are discussed. The second allows a decrease in the hardware cost of the fuzzy system and in the computing time of the final result (fuzzy or crisp), especially when referring to relational systems. The physical architecture consists of IP modules implemented in an FPGA structure. The modules can be inserted into or removed from the project to get a desirable fuzzy logic controller configuration. The fuzzy inference system implemented in FPGA can operate with a much higher performance than software implementations on standard microcontrollers.

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“…Test waveforms can also be generated using the same constructs. Moreover all the constructs may be combined together to provide a comprehensive description of the system in a single model [1]. A modeling approach for describing fuzzy controllers using statecharts and VHDL has been proposed in [7,14].…”

Section: Introductionmentioning

confidence: 99%

VHDL Realization of Hybrid Control Strategy for a Nonlinear System

Kalloor¹,

Meyyappan²

2015

IJCA

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The Process Industries are automated to keeping in tune with the changing requirements. It creates the need of a well defined philosophy to cater to the extent of sophistication. The Scheme projects a mechanism to adapt to the evolving scenario and orient a strategy to accomplish the desired objective. A conical tank system is chosen and a methodology designed to eclipse the specified liquid level in it through appropriate hydraulic arrangements. It augurs the need of a well defined control algorithm to charter a corrective action and seeks the role of a state of the art processor to implement the procedure. The self tuning Fuzzy-PI control algorithm is coded using VHDL and is evaluated through Modlsim based simulation to verify its practical viability.

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FPGA-Based Fuzzy Logic: Design and Applications – a Review

Cited by 43 publications

References 0 publications

Literature Review for Digital Implementations of Fuzzy Logic Type-1 and Type-2

Literature Review for Digital Implementations of Fuzzy Logic Type-1 and Type-2

Decomposition of the fuzzy inference system for implementation in the FPGA structure

VHDL Realization of Hybrid Control Strategy for a Nonlinear System

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