Browsing by Author "Babawuro, Adamu Y."

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    CONTROL OF PARTICULATE MATTER (PM) EMISSIONS FROM INDUSTRIAL PLANT USING ANFIS BASED CONTROLLER
    (ARPN Journal of Engineering and Applied Sciences, 2006) Umar, Sambo A.; Babawuro, Adamu Y.; Salami, Momoh-Jimoh E.; Khan, Md Raisuddin
    In recent times, the negative effect of air pollution such as particulate matter (PM) emitted from industrial plants has compelled researchers in finding efficient control system to control such pollutants in order to keep the environment safe. The aim of this study is to develop a reliable method of controlling the emissions of PM using wet scrubber system as a control device. The process of a wet scrubber is nonlinear in nature. Due to difficulty in selecting optimum scrubbing liquid droplet size in wet scrubbing process, the system becomes complex. Thus, Adaptive Neuro Fuzzy Inference System (ANFIS) based control technique is employed in this paper to handle the nonlinearities. ANFIS control technique has the advantage to integrate fuzzy logic systems and learning ability of neural network, thus able to handle nonlinear systems better. The controller is developed using data of PM emission from cement kiln. The system is simulated using triangular and trapezoidal membership function (MF) with 2 and 3 input MF in each case. The performance of the controller is evaluated based on settling time. The results indicated that the developed controller was able to maintain the PM emission below a set point of 20µg/m3 which is the maximum allowable PM emission limit recommended by world health organization (WHO). The controller with 2 input triangular membership functions indicated a better performance with a settling time of 5.2 seconds.
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    Fuzzy logic based intelligent temperature controller for cassava post-harvest storage system
    (International Conference on Artificial Intelligence, Electrical & Electronics Engineering (AIEE ‘15), 2015-05-14) Babawuro, Adamu Y.; Umar, Sambo A.; Fatai, Sado; Salami, Momoh-Jimoh E.; Sidek, S. N.
    Significant amount of stored agricultural products are lost as a result of poor and inefficient storage systems in most developing countries, especially in tropical regions of the world. Improvements on the existing storage methods is important to guarantee food security. This study proposes the development of intelligent temperature control technique for fresh cassava roots crop post-harvest storage system using fuzzy logic controller (FLC). The intelligent controller which has two inputs (error in temperature and rate of change in the error) and one output (change in fan speed) was simulated with the developed storage system model for temperature control of fresh cassava roots crop. The results obtained shows that the controller can track appropriately the reference temperature and also gives good stability and robustness towards input disturbances. Faster response to maintain the storage temperature within acceptable limit close to reference point was also achieved successfully.
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    Fuzzy Logic Controller (FLC) for the control of Particulate Matter (PM) emission in wet scrubber system
    (Proceedings of the International Conference on Computer, Electrical and Electronics, 2015-05-13) Umar, Sambo A.; Babawuro, Adamu Y.; Sado, Fatai; Salami, Momoh-Jimoh E.; Khan, Md Raisuddin
    Air pollution such as particulate matter (PM) emitted from industries result in several thousands of deaths. In recognition of this global threat, a large number of abatement measures have been taken to minimize the emission of this pollutant. Wet scrubber system has been the most widely used control device for PM contaminants. Its operating variables (gas velocity, temperature profile, particle size, liquid droplet’s size, terminal settling velocity of liquid droplets, particle density and liquid to gas ratio) fluctuates randomly, thus resulting in a non-linear dynamic behavior of the system. This non-linearity generally limits the ability of the scrubber to control PM less than 5µm in diameter. Thus, in this study, intelligent control technique based on fuzzy logic controller (FLC) has been developed to solve the non-linearity in the system by selecting appropriate scrubbing liquid droplet size in order to improve system performance to control PM that are less than 5µm in diameter. The developed FLC has two inputs (error and change in error) and a single output. The results shows that within short settling time, the controller was able to effectively reduce the PM that are less than 5µm below the set-point (20µg/m3) which is the maximum allowable emission limit of PM contaminants by world health organization (WHO).