Locating a two-wheeled robot using extended Kalman filter

Kalman filter je vrlo općenita metoda filtriranja kojom se mogu riješiti problemi kao što su optimalna procjena, predviđanje, filtriranje buke i optimalna kontrola. Problem koji se javlja kod detekcije ispravne putanje gibajućih predmeta je prijem bučnih podataka. Stoga je moguće da se informacije neispravno pronađu. Postoje razne metode za dobivanje ispravnih podataka iz primljene obavijesti. U ovom radu cilj je otkriti putanju robota s dva kotača primjenom proširenog Kalman filtera. U tu su se svrhu rabile trokutaste, kružne, eliptične i sinusoidne putanje u istraživanju raznih scenarija. Rezultati pokazuju da se Kalmanovim filterom optimalno pronalazi ispravna putanja s manje od 3 % učestalosti pogreške. Ti rezultati također pokazuju da učestalost pogreške kod pronalaženja kružnih i trokutastih putanja ima najvišu i najnižu vrijednost primjenom Kalman filtera; uz to, rezultati su pokazali da učestalost pogreške uvelike ovisi o promjenama putanje.The Kalman filter is a very general method of filtering which can solve problems such as optimal estimation, prediction, noise filtering, and optimal control. A problem with detection of correct path of moving objects is the received noisy data. Therefore, it is possible that the information is incorrectly detected. There are Different methods to extract the correct data from the received information. This paper aims to detect the path of a two-wheeled robot using extended Kalman filter. For this purpose, triangular, circular, elliptical, and Sinusoidal paths were used to explore various scenarios. The results showed that the Kalman filter optimally detects the correct path with less than 3 % error rate. These results also show that error rate related to detect circular and triangular paths has the highest and lowest value, respectively, using the extended Kalman filter; in addition, the results showed that the error rate strongly depends on path changes

Catalytic Potential of Nano-Magnesium Oxide on Degradation of Humic Acids From Aquatic Solutions

Catalytic ozonation is a new and promising process used to remove the contaminants from drinking water and wastewater. This study aimed to evaluate the catalytic potential of nano-magnesium oxide (nano-MgO) for the removal of humic acids (HA) from water. Mg (NO3)2 solution was used to prepare MgO powder by the calcination method. In a semi-batch reactor, the catalytic ozonation was carried out. The effects of the various operating parameters, including pH, reaction time, T-butyl alcohol (TBA) and phosphate on HA degradation were evaluated. Experimental results indicated that degradation of HA was increased as the pH solution and reaction time were increased. Maximum HA degradation was obtained at pH = 10 and the reaction time of 10 minutes in the catalytic process. The calculated catalytic potential of nano-MgO on ozonation of HA was 60%. Moreover, catalytic ozonation process was not affected by TBA and the main reaction on HA degradation HA have effect take place on MgO surface. According to the results of this study, the developed MgO catalyst is the active and proficient catalyst in HA degradation using the catalytic ozonation process