The tradeoff between accuracy and interpretability in fuzzy modeling has shifted into focus in last few years. This paper aims at improving accuracy of linguistic models while maintaining a good interpretability. A new gradient-based method, extended version of Jager approach, is proposed for the optimization of transparent Mamdani systems. The advantage of Mamdani systems if compared to 0 orde...

This paper describes the development and tuning methods for a novel self-organizing fuzzy proportional integral derivative (PID) controller. Before applying fuzzy logic, the PID gains are tuned using a conventional tuning method. At supervisory level, fuzzy logic readjusts the PID gains online. In the first tuning method, fuzzy logic at the supervisory level readjusts the three PID gains during...

Load sensor is developed using mamdani type fuzzy model. It is two input one output model. Inputs taken for the load sensor are load and displacement and voltage is taken as output. The model is simulated using MATLAB Fuzzy Logic Toolbox and simulation results are shown in this paper. Index Terms —Fiber Bragg Grating sensor, Fuzzy logic, Load sensor, Mamdani, Windmill blades.

The paper presents the results of FPGA implementation of fuzzy Mamdani system with parametric conjunctions generated by monotone sum of basic t-norms. The system is implemented on the DE2 Altera development board using VHDL language. The system contains reconfigurable fuzzy Mamdani model with parametric membership functions and parametric operations that gives possibility to adjust the system t...

The Mamdani model [1] of Fuzzy Systems is the earliest and the most widely studied type of Fuzzy Systems. In this work, Residuated Implication (R-implication) operators have been explored for rule reduction in Mamdani-Type Fuzzy Systems with lossless inferencing.

The paper presents the results of FPGA implementation of fuzzy Mamdani system with parametric conjunctions generated by monotone sum of basic t-norms. The system is implemented on the DE2 Altera development board using VHDL language. The system contains reconfigurable fuzzy Mamdani model with parametric membership functions and parametric operations that gives possibility to adjust the system t...

This paper proposes financial time-series forecasting using a feature selection method based on the non-overlap area distribution measurement method supported in a neural network with weighted fuzzy membership functions (NEWFM) and the TakagiSugeno (T-S) fuzzy model. The non-overlap area distribution measurement method selects the minimum number of features with the highest performance by remov...

Air conditioning system is developed using mamdani fuzzy model and neuro fuzzy model. It is two input one output system where inputs being the temperature and humidity measured from their respective sensors and the output being the signal that controls the compressor speed. Both the models are simulated using MATLAB Fuzzy logic Toolbox and their results are compared. Keywords— air conditioning,...

Professor Ebrahim (Abe) Mamdani died on January 22, 2010. He was born in Tanzania in June 1942 and educated in India, he went to UK in 1966. After obtaining his PhD at Queen Mary College, University of London, he joined its Electrical Engineering Department, where he developed the first fuzzy controller. In the mid-eighties he moved to Imperial College, where he was now an Emeritus Professor. I...