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Design and Optimization of Fuzzy-based Digital FIR Kernel Filter for Real-Time Control Applications

Journal: International Journal of Scientific Engineering and Science (Vol.5, No. 10)

Publication Date:

Authors : ;

Page : 8-19

Keywords : FIR Filter; MATLAB; Greenhouse; Low pass; high pass; Convolution; Fuzzy logic; Temperature; Humidity;

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21st century farmers are prone to the dangers of climatic changes resulting from intense temperature and relative humidity in their nursery beds of fruits and vegetables. For optimum growth of those fruits and vegetables without having to visit their farms often, digital FIR filters that control the Low pass frequency threshold at 0.3???? rad/time span , blocking the high pass frequency signal at 0.7 ???? rad/time span as well as control the high pass frequency threshold at 0.7???? rad/time span , blocking the low pass frequency signal at 0.3 ???? rad/time span were designed, employing optimization methods such as Least square method, Parks McClellan Algorithm and window methods setting the filter length of 200 samples; galvanized with convolution techniques. It is interesting to know that the digital FIR filters with built-in temperature and humidity sensors control fuzzy filtering (using Gaussian membership function with 6 base rules) in the greenhouse nursery bed; hence the name Fuzzy Digital FIR kernel Filter for Real-time control Applications. The temperature and relative humidity of the next-generation greenhouse been controlled are in the range of 15-30℃ and 50-90% respectively. All through the design, MATLAB fuzzy logic, DSP, Filter tool boxes and MATLAB File editor (M-File) were utilized for the simulation, modeling and generation of C-programming codes.

Last modified: 2021-11-25 19:00:30