Design and application of an analog fuzzy logic controller

Guo, S.; Peters, L.; Surmann, Hartmut

doi:10.1109/91.544303

Cited by 93 publications

(45 citation statements)

References 19 publications

(26 reference statements)

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“…Circuit blocks and design techniques for CMOS analog fuzzy controllers have been reported elsewhere [13]- [17].…”

mentioning

confidence: 99%

“…Some of them have been demonstrated through actual monolithic circuits, a fraction of which include programmability [15]- [17]. However, although precision is a weak point of the analog approach, most previous contributions do not consider the accuracy issue during the design phase.…”

mentioning

confidence: 99%

“…The demonstration chip in this paper implements more rules than previous analog monolithic controllers and features much smaller values, namely: 470 ns 8.6 mW (with 16 rules) versus 570 ns 44 mW (with 9 rules) [16], and 160 ns 550 mW (with 13 rules) [17]. Programmability is also a quality of our chip, which incorporates on-chip memories for serial digital programming of the rule consequents, and allows external analog programming of the membership functions.…”

mentioning

confidence: 99%

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A modular programmable CMOS analog fuzzy controller chip

Rodríguez-Vázquez

Navas

Delgado‐Restituto

et al. 1999

IEEE Trans. Circuits Syst. II

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Abstract-We present a highly modular fuzzy inference analog CMOS chip architecture with on-chip digital programmability. This chip consists of the interconnection of parameterized instances of two different kind of blocks, namely label blocks and rule blocks. The architecture realizes a lattice partition of the universe of discourse, which at the hardware level means that the fuzzy labels associated to every input (realized by the label blocks) are shared among the rule blocks. This reduces the area and power consumption and is the key point for chip modularity. The proposed architecture is demonstrated through a 16-rule twoinput CMOS 1-m prototype which features an operation speed of 2.5 Mflips (2.5 2 2 2 10 6 fuzzy inferences per second) with 8.6 mW power consumption. Core area occupation of this prototype is of only 1.6 mm 2 including the digital control and memory circuitry used for programmability. Because of the architecture modularity the number of inputs and rules can be increased with any hardly design effort.

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“…Circuit blocks and design techniques for CMOS analog fuzzy controllers have been reported elsewhere [13]- [17].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A modular programmable CMOS analog fuzzy controller chip

Rodríguez-Vázquez

Navas

Delgado‐Restituto

et al. 1999

IEEE Trans. Circuits Syst. II

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“…In an irregular battle zone, these deficiencies decrease the performance of the UGV; therefore, virtual reality (VR)-based weapon systems provide an efficient way to make the shooting process more realistic. Oculus VR headset is a widely used commercial product, which supplies three-dimensional image data for users [1]. One can feel as if he/she is in the VR environment using the headset.…”

Section: Introductionmentioning

confidence: 99%

Virtual-reality-based remote-controlled mobile robot platform

Karakaya¹,

Akkaya²,

Sekerci³

et al. 2017

GJCS

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In this paper, a mobile robot system, which consists of a moving base and a built-in weapon platform, was developed. The base is controlled manually using a wireless joystick in which the remote hand weapon manipulates the built-in weapon platform. A stereo vision camera is mounted on the front plane of the built-in weapon platform. Real-time video of the battle zone is recorded by the stereo camera module and is simultaneously monitored on virtual reality glasses. The glasses are worn by the person who will control the built-in weapon. The remote hand weapon is also held by the same person, and the real-time motion directories of the hand weapon are transmitted to the main platform via user datagram protocol. The builtin weapon is fired when the remote user triggers the hand weapon. The weapon platform is locked to the target, regardless of the moving base of the mobile robot.

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“…Different implementations of fuzzy systems have been proposed, including digital [2], [3], as well as analog [4], [5] alternatives.…”

Section: Introductionmentioning

confidence: 99%

Analog sequential architecture for neuro-fuzzy models VLSI implementation

Moreno

Madrenas

Alarcón

et al. 1997

Lecture Notes in Computer Science

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An analog sequential architecture for efficient neuro-fuzzy models implementation is proposed. The best features of digital and analog domains are combined to provide a high degree of flexibility (in terms of number of inputs, number of membership functions per input and number of fuzzy rules) when handling real world tasks. The performance estimations show a good area/throughput ratio, thus making the architecture suitable for a wide range of applications.

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Design and application of an analog fuzzy logic controller

Cited by 93 publications

References 19 publications

A modular programmable CMOS analog fuzzy controller chip

A modular programmable CMOS analog fuzzy controller chip

Virtual-reality-based remote-controlled mobile robot platform

Analog sequential architecture for neuro-fuzzy models VLSI implementation

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