PublisherUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
Rights accessOpen Access
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 low-medium complexity. This paper presents a strategy to preserve most
of the advantages of an analog implementation, while allowing a notorious increment of the system complexity.
Such strategy consists in implementing a reduced number of rules, those that really determine the output in a lattice controller, which we call analog core, then this core is dynamically programmed to
perform the computation related to a specific rule set. The data to program the analog core are stored in a memory, and
constitutes the whole knowledge base in a kind of virtual rule set. An example 64-rule,
2-input, 4-bit singleton controller has been designed in a CMOS 0.7$\mu$mm technology to demonstrate the viability
of the architecture. The measured input-output delay is around 500ns for a power consumption of 16mW and a chip area (without pads) of 2.65mm$^2$.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder. If you wish to make any use of the work not provided for in the law, please contact: firstname.lastname@example.org