Low power membership function generator for interval type-2 fuzzy system

An analog type-2 fuzzy membership function generator is analyzed, while its low power features are demonstrated. Developed and designed to work as part of an energy-efficient type-2 fuzzy system (i.e. controller, neural network), it operates in current-mode, allowing multiple settings, such as: variable shape, position, slope and size of the Footprint of Uncertainty. All these parameters can be updated/adjusted during actual operation, being suitable for real-time applications, even with online learning. The achieved robustness and flexibility of the architecture allow operation with different values of supply voltage and maximum degree of membership current. Simulations based on CADENCE software were performed to assess the functionalities. The circuit was prototyped in TSMC CMOS 0.18 mu m technology and experimental results show a power consumption of 72.56 mu W, 7.86 mu W, and 478.1nW when operating with power supplies of 1.2V, 1V, and even with 0.6V, respectively, much less than the nominal supply voltage of the TSMC CMOS 0.18 mu m technology (1.8V). These results attest the circuit is robust, low-power, functional and suitable for systems that require energy efficiency, presenting a high potential for practical implementations including those that require real-time dedicated hardware.