This paper reports the design and implementation of genetically optimized fuzzy logic controller (GAFLC) for split air-conditioner based on the principle of Fanger’s Predicted Mean Vote (PMV) index. The proposed control strategy is aimed at improving the indoor thermal environment (ITE) at houses, offices, libraries, hotels, etc. because it plays a vital role in determining the health, physical and mental productivity of the occupants. The GAFLC has been implemented in MATLAB Simulink for computer simulation and also on hardware platform using the commercially available 8-bit ATmega-328 microcontroller through embedded C-coding for real practice. One part of the designed control algorithm examines the values of activity level, clothing insulation, air velocity, and relative humidity and decides the comfort temperature value to be set such that the PMV and PPD indices get satisfied. The other part generates a control signal to the air-conditioner compressor to maintain that temperature. From the simulation results it is seen that the generated comfort temperature values are in the range of 24.4∘– 26.55∘C for various combinations of environmental and personal parameters, which are well above the general temperature set value of 20∘C. This indicates the scope for reducing energy consumption to a greater extent. Also the PMV index lies in the range of [Formula: see text]0.23 to +[Formula: see text]0.36 with untuned fuzzy inference system (FIS), and in the range of [Formula: see text]0.32 to +[Formula: see text]0.14 with genetic algorithm (GA)-tuned FIS, which are acceptable comfort levels that human physiology can endure with more satisfaction. The experimental results show that GAFLC has generated a comfort temperature value for specified input parameters and also maintained the room temperature at that value to keep the thermal ambience more satisfactorily.

In industrial automation, motor control technique plays the vital role. Motor consists of inductor or electromagnet. Causing inductor or electromagnet, magnetic inductions are produces which resists any change of motor speed. Hence, according to set point, precise speed control is challenging. However, using various control technique can be controls the speed of DC motor. The aim of the present paper is to implement hardware and control the speed of DC motor using embedded fuzzy logic. Set point have been applied externally and recorded the speed of motor through opto-isolator sensor module. In the hardware of DC motor control keypad, 2x16 LCD, DC motor driver and opto-isolator module are interfaced to PIC microcontroller. The Fuzzy algorithm is embedded in the microcontroller wherein input fuzification signals ‘error (Δe)’ and ‘change in error (e(n))’ and output fuzification signal ‘PWM’. The both of inputs of fuzzy algorithm are varied and record output of fuzzy algorithm which is PWM. Moreover, the hardware implementation has been tested for real time control of DC Motor.