The identification of plant species using spectrometry is utilized in various applications. Some researchers have reported the success of using the reflectance spectrum along with its derivatives and their coding to identify different Phenomena, including plants. In this study, based on these parameters, we developed a new method to improve the accuracy of identifying plant species. Two experimental datasets (LOPEX and ANGERS) containing the leaf reflectance spectrum of different plant species from different families were used. The proposed method includes two main stages. In the first stage, the unique regions of wavelengths were found for each plant family. By comparing an unknown species with each family only in the specified regions and coding results with the innovative coding method named Coding Based on Selected Threshold (CBSeT) and used similarity criteria, the family of unknown specie is determined. In the second step, similarly unique regions were found to separate the species within a family from each other using species standard deviation analysis, and the type of unknown species was similarly identified. The obtained results for the identification of plant species of unknown spectra show the accuracies of 91.66% and 90% for the proposed method with Similarity Coding Index (SCI) and Spectral Angle Mapper (SAM) criteria respectively. These numbers are more acceptable results compared to the other reflectance coding methods such as Spectral analysis manager (SPAM), Spectral feature-based binary coding (SFBC), Spectral derivative feature coding (SDFC), Spectral feature probabilistic coding (SFPC) with 38%, 37%, 29%, and 20% of accuracies improvement respectively.
In this article, based on feedback linearization using Lyapunov design method, an adaptive controller is proposed for an Aerial Robot or unmanned aerial vehicle (UAV). After introducing a nonlinear dynamics model of the system in case of longitudinal equations, comparing controllers are designed to manage the system performance during various maneuvers. Also, stability analysis for the designed adaptation law is studied and discussed. To evaluate the performance of designed controllers for a given system, a comprehensive simulation program is developed. One of the most important results of this study is that tracking errors for the two state variables exponentially converge to zero, even in the presence of parameters uncertainty. Therefore, it is shown that the proposed adaptive controller is able to perform perfect path tracking maneuvers.
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