Hardware implementation of interval type-2 fuzzy logic controller

Mesri, Alireza; Khoei, Abdollah; Hadidi, Khayrollah

doi:10.1109/iraniancee.2013.6599656

Cited by 5 publications

(3 citation statements)

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“…10 shows the ideal output in terms of the duty cycle as a function of the two inputs. Considering an inference engine that outputs the firing intervals of the consequents in current-mode, in the range [0,10µA], such as in [14], [19], [37], it is possible to simulate the response of the proposed circuit and similarly plot its output as a function of the two inputs of the system. The result is shown in Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Analog type-2 fuzzy controllers found in the literature generally implement the expression in (3) with multiplier/divider circuits operating in current-mode [19], [20]. Equation (3) is very similar to a Center-of-Sets defuzzification, and most type-1 analog defuzzifiers also operate with multiplier/divider circuits in current-mode [25], [26], voltage mode [27], and some with current-input and voltage-output circuits [28]- [30].…”

Section: Type-reduction Pwm Architecturementioning

confidence: 99%

“…A method of type-reduction for interval type-2 inference systems, proposed as a closed-form alternative to the iterative algorithms (such as the Karnik-Mendel [15] and Wu-Mendel methods [16]), is called the Nie-Tan method (NT) [17] and is particularly well suited for analog hardware implementations. The accuracy of the NT method has been demonstrated [18], and while some analog controllers have already employed it using current-mode multiplier/divider circuits [19]- [21], the design process of multiplier/dividers must deal with several non-linear effects, such as mismatch and channel-length modulation, that can degrade the performance of the circuit.…”

Section: Introductionmentioning

confidence: 99%

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A PWM Nie-Tan Type-Reducer Circuit for a Low-Power Interval Type-2 Fuzzy Controller

2021

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A novel Type-Reduction/Defuzzification circuit architecture for an analog interval type-2 fuzzy inference system is proposed. Based on the Nie-Tan type-reduction method, the circuit operates with current-mode inputs, representing the firing intervals of the rules created by the inference engine, and generating a PWM output. It is demonstrated that by selecting an appropriate number of consequents it is possible to create the PWM output directly, without the need for analog multiplier/divider circuits. This feature makes the circuit very simple, aiding in the design process, while the PWM output makes it suitable for controlling DC-DC converters, maximum power point trackers (MPPT) for energy generators, or other switching applications. It is designed to achieve very low power consumption, allowing its use in power restrained environments, such as energy harvesting systems. The circuit was designed using TSMC 0.18µm technology, in CADENCE Virtuoso software, and simulated for different combinations of input values, demonstrating its capabilities. It was also simulated as part of a type-2 fuzzy inference system with two inputs, nine rules, and firing intervals represented by currents within 0 and 10µA. The circuit was prototyped, and the experimental average power consumption was only 53.8µW, validating its low power consumption characteristic.

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Section: Simulation Resultsmentioning

confidence: 99%