VIDAL VERDÚ , Fernando

This paper focus on the design of adaptive mixed-signal fuzzy chips. These chips have parallel architecture and feature electrically-controlable surface maps. The design methodology is based on the use of composite transistors - modular and well suited for design automation. This methodology is supported by dedicated, hardware-compatible...

We present a parallel architecture for fuzzy controllers and a methodology for their realization as analog CMOS chips for low- and medium-precision applications. These chips can be made to learn through the adaptation of electrically controllable parameters guided by a dedicated hardware-compatible learning algorithm. Our designs emphasize...

Analog circuits are natural candidates to design fuzzy chips with optimum speed/power figures for precision up to about 1%. This paper presents a methodology and circuit blocks to realize fuzzy controllers in the form of analog CMOS chips. These chips can be made to adapt their function through electrical control. The proposed design...

Fuzzy controllers are able to incorporate knowledge expressed in if-then rules. These rules are given by experts or skilful operators. Problems arise when there are no experts or/and rules are not easy to find. Author's proposal consists on an analog fuzzy controller which accepts structured language as well as input/output data pairs, thus...

Learning algorithms have become of great interest to be applied not only to neural or hybrid neuro-fuzzy systems, but also as a tool to achieve a fine tuning of analog circuits, whose main drawback is their lack of precision. This paper presents accurate, discrete-time CMOS building blocks to implement learning rules on-chip. Specifically, a...

Presents a mixed-signal fuzzy controller chip and its application to control of DC motors. The controller is based on a multiplexed architecture presented by the authors (1998), where building blocks are also described. We focus here on showing experimental results from an example implementation of this architecture as well as on illustrating...

This Paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input-output delay and precision performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts. This combination of performance and complexity is achieved through the use of a mixed-signal...

The low/medium precision required for many fuzzy applications makes analog circuits natural candidates to design fuzzy chips with optimum speed/power figures. This paper presents a sixteen rules-two inputs analog fuzzy controller in a CMOS 1 /spl mu/m single-poly technology based on building blocks implementations previously proposed by the...

Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements. This limit in precision as well as the lack of design tools when compared to the digital approach, imposes a limit of complexity, hence fuzzy analog controllers are usually oriented to fast low-power systems with...

Analog circuits are natural candidates to design fuzzy chips with optimum speed/power figures for precision up to about 1%. This paper presents a methodology and circuit blocks to realize fuzzy controllers in the form of analog CMOS chips. These chips can be made to adapt their function through electrical control. The proposed design...

Limited precision imposes limits on the complexity of analogue circuits, and hence fuzzy analogue controllers are usually oriented to fast low-power systems with low-medium complexity. A strategy to preserve most of the advantages of an analogue implementation, while allowing a marked increment in system complexity, is presented.

Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements [1]. This limit in precision, as well as the lack of design tools when compared to the digital approach, imposes a limit of complexity, hence fuzzy analog controllers are usually oriented to fast low-power systems with...

We present a fuzzy inference chip capable to evaluate 16 programmable rules at a speed of 2.5Mflips (2.5 × 10 6 fuzzy inferences per second) with 8.6mW power consumption. It occupies 2.89mm 2 (including pads) in a CMOS 1μm single-poly technology. Measurements are given to demonstrate its performance. All the operations needed for fuzzy...

We present a highly modular fuzzy inference analog CMOS chip architecture with on-chip digital progranirnability. 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...

This paper presents a bioinspired integrated tactile coprocessor that is able to generate a warning in the case of slippage via the data provided by a tactile sensor. Some implementations use different layers of piezoresistive and piezoelectric materials to build upon the raw sensor and obtain the static (pressure) as well as the dynamic...

Outlines a systematic approach to design fuzzy inference systems using analog integrated circuits in standard CMOS VLSI technologies. The proposed circuit building blocks are arranged in a layered neuro/fuzzy architecture composed of 5 layers: fuzzification, T-norm, normalization, consequent, and output. Inference is performed by using Takagi...

Artificial sensitive skins are intended to emulate the human skin to improve the skills of robots and machinery in complex unstructured environments. They are basically smart arrays of pressure sensors. As in the case of artificial retinas, one problem to solve is the management of the huge amount of information that such arrays provide,...

The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in tele-presence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision...

The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in telepresence, minimal invasive surgery, robotics etc. The array of pressure data provided by these devices can be treated with different image processing algorithms to extract the required information. However, as in the case of...