Effects of fractional order on performance of fosmc for speed control of PMSM

Fractional order sliding mode control has been applied for speed control of PMSM. However, in many previous works, the effects of the controller's parameters have not been studied. This paper investigates the effects of fractional order on performance of FOSMC speed control of PMSM. In this work, fractional order, α and β of FOSMS-PID were varied, and their performances were compared. The simulation and experimental results show that variation of order of fractional order integration, α and order of fractional order differentiation, β can affect the performance of the FOSMC-PID controller. Selection of α and β values determines balancing strategies between integral and differentiation portion of the controller. Proper value selection and combination of these variables can further contribute to obtain optimum speed tracking, disturbance rejection and chattering reduction abilities

A hybrid thermal-visible fusion for outdoor human detection

Multisensory image fusion can be used to improve the visual interpretability of an image for further processing task. A hybrid thermal-visible image fusion is proposed in this paper to detect the target and produce an output image that had all the information from both sensors. The thermal target region was extracted using Niblack algorithm and some morphological operators. Then, the source images were decomposed at pixel level using Stationary Wavelet Transform (SWT). The appropriate fusion rule were chosen for low and high frequency components and finally the fused image was obtained from inverse SWT. Results show that the proposed method achieve better to include figure of merit than the other three methods

Chemometric Classification Of Herb � Orthosiphon Stamineus According To Its Geographical Origin Using Virtual Chemical Sensor Based Upon Fast GC

An analytical method using Electronic Nose (E-nose) instrument for analysis of volatile organic compound from Orthosiphon stamineus raw samples have been developed

Fusion of thermal and visible imagery for effective detection and tracking of salient objects in videos

In this paper, we present an efficient approach to detect and track salient objects from videos. In general, colored visible image in red-green-blue (RGB) has better distinguishability in human visual perception, yet it suffers from the effect of illumination noise and shadows. On the contrary, thermal image is less sensitive to these noise effects though its distinguishability varies according to environmental settings. To this end, fusion of these two modalities provides an effective solution to tackle this problem. First, a background model is extracted followed by background-subtraction for foreground detection in visible images. Meanwhile, adaptively thresholding is applied for foreground detection in thermal domain as human objects tend to be of higher temperature thus brighter than the background. To deal with cases of occlusion, prediction based forward tracking and backward tracking are employed to identify separate objects even the foreground detection fails. The proposed method is evaluated on OTCBVS, a publicly available color-thermal benchmark dataset. Promising results have shown that the proposed fusion based approach can successfully detect and track multiple human objects

Fractional order sliding mode controller based on supervised machine learning techniques for speed control of PMSM

Tracking the speed and current in permanent magnet synchronous motors (PMSMs) for industrial applications is challenging due to various external and internal disturbances such as parameter variations, unmodelled dynamics, and external load disturbances. Inaccurate tracking of speed and current results in severe system deterioration and overheating. Therefore, the design of the controller for a PMSM is essential to ensure the system can operate efficiently under conditions of parametric uncertainties and significant variations. The present work proposes a PMSM speed controller using machine learning (ML) techniques for quick response and insensitivity to parameter changes and disturbances. The proposed ML controller is designed by learning fractional-order sliding mode control (FOSMC) controller behavior. The primary purpose of using ML in FOSMC is to avoid the self-tuning of the parameters and ensure the speed reaches the reference value in finite time with faster convergence and better tracking precision. Furthermore, the ML model does not require the mathematical model of the speed controller. In this work, several ML models are empirically evaluated on their estimation accuracy for speed tracking, namely ordinary least squares, passive-aggressive regression, random forest, and support vector machine. Finally, the proposed controller is implemented on a real-time hardware-in-the-loop (HIL) simulation platform from PLECS Inc. Comparative simulation and experimental results are presented and discussed. It is shown from the comparative study that the proposed FOSMC based on ML outperformed the traditional sliding mode control (SMC), which is more commonly used in industry in terms of tracking speed and accuracy

Image Enhancement using Thermal-visible Fusion for Human Detection

An increased interest in detecting human beings in video surveillance system has emerged in recent years. Multisensory image fusion deserves more research attention due to the capability to improve the visual interpretability of an image. This study proposed fusion techniques for human detection based on multiscale transform using grayscale visual light and infrared images. The samples for this study were taken from online dataset. Both images captured by the two sensors were decomposed into high and low frequency coefficients using Stationary Wavelet Transform (SWT). Hence, the appropriate fusion rule was used to merge the coefficients and finally, the final fused image was obtained by using inverse SWT. From the qualitative and quantitative results, the proposed method is more superior than the two other methods in terms of enhancement of the target region and preservation of details information of the image

Comparison of Human Segmentation using Thermal and Color Image in Outdoor Environment

Nowadays video surveillance system are very important in an urban and rural area that can operate day and night, in all weather conditions. It is a challenging task to detect human due to body size, occlusion, lighting conditions, cluttered background, cloth texture and similarity of the human body/clothing with the background. Hence, in this paper, thermal and color images are utilized to evaluate the performance of the proposed method for single human segmentation in outdoor environment. The evaluation of the segmentation process is carried out based on OTCBVS Benchmark Dataset. The approach use morphological operation, global thresholding and edge detection as the main step in segmentation process. For quantitative analysis, 100 images for color and thermal respectively are analyze using Jaccard Similarity Coefficient where we compare the resulting image with its ground truth. From the results, human segmentation using thermal images are better compared to color image where 88% show a good segmentation result and only 4% cannot get a human figure correctly

Preliminary Study of Student Performance on Algebraic Concepts and Differentiation.

Teaching on differentiation topic is paramount important for science and engineering students at first year tertiary level.However lectures are facing difficulty when students are unable to apply the concepts and basic problem solving skills on differentiation when applied to science and engineering related problems at higher level. The aim of this study is to determine students’ performances on algebraic and differentiation concept. An analysis had been carried out to identify the algebraic concepts in solving mathematical equations and to relate the misconceptions with the basic technical errors done in solving the first derivatives. Two sets of questionnaires had been distributed; Questionnaire I for Additional Mathematics teachers and Questionnaire II for form four students (n = 113) in three selected secondary schools (an urban school, two rural schools) in the district of Kuantan, Pahang. Findings of the study revealed that the students’ performance in solving algebraic is better than students’ performance on differentiation problems

A Hybrid Thermal-Visible Fusion for Outdoor Human Detection

Multisensory image fusion can be used to improve the visual interpretability of an image for further processing task. A hybrid thermal-visible image fusion is proposed in this paper to detect the target and produce an output image that had all the information from both sensors. The thermal target region was extracted using Niblack algorithm and some morphological operators. Then, the source images were decomposed at pixel level using Stationary Wavelet Transform (SWT). The appropriate fusion rule were chosen for low and high frequency components and finally the fused image was obtained from inverse SWT. Results show that the proposed method achieve better to include figure of merit than the other three methods

A Hybrid Thermal-visible Fusion for Outdoor Human Detection

Multisensory image fusion can be used to improve the visual interpretability of an image for further processing task. A hybrid thermal-visible image fusion is proposed in this paper to detect the target and produce an output image that had all the information from both sensors. The thermal target region was extracted using Niblack algorithm and some morphological operators. Then, the source images were decomposed at pixel level using Stationary Wavelet Transform (SWT). The appropriate fusion rule were chosen for low and high frequency components and finally the fused image was obtained from inverse SWT. Results show that the proposed method achieve better to include figure of merit than the other three methods