Anwar Hasni Abu Hassan

A comparative study of PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc motor drive

This paper presents the comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed control of brushless dc (BLDC) motor. The control structure of the proposed drive system is described. The simulation results of the drive system for different operation modes are evaluated and compared. A fuzzy controller offers better speed response for start-up while PI controller has good compliance over variation of load torque but has slow settling response. Hybrid controller has an advantage of integrating a superiority of these two controllers for better control performances. Matlab/Simulink is used to carry out the simulation.

Stereo matching algorithm based on per pixel difference adjustment, iterative guided filter and graph segmentation ☆

Stereo matching process is a difficult and challenging task due to many uncontrollable factors that affect the results. These factors include the radiometric variations and illumination inconsistence. The absolute differences (AD) algorithms work fast, but they are too sensitive to noise and low textured areas. Therefore, this paper proposes an improved algorithm to overcome these limitations. First, the proposed algorithm utilizes per-pixel difference adjustment for AD and gradient matching to reduce the radiometric distortions. Then, both differences are combined with census transform to reduce the effect of illumination variations. Second, a new approach of iterative guided filter is introduced at cost aggregation to preserve and improve the object boundaries. The undirected graph segmentation is used at the last stage in order to smoothen the low textured areas. The experimental results on the standard indoor and outdoor datasets show that the proposed algorithm produces smooth disparity maps and accurate results.

Analytical modeling of permanent magnet excited brushed DC motor for low-cost applications

In this paper, we present an analytical modelling of permanent magnet excited brushed DC motor for cost sensitive applications. General solutions to the Laplacian/quasi-Poissonian magnetic field equations are first derived in the motor airgap. Applying the specified boundary conditions, normal and tangential components of flux density in the airgap can be analytically predicted. With distributed windings employed in the armature slots, their flux linkage, induced voltage and motor performance can also be calculated. The proposed analytical model can also be used to parameterize the brushed DC motor for optimal performance such as minimum torque ripple. The proposed model shows very good agreement with the results obtained from FEM. Furthermore, the analytical model compares the calculated results between the 12- slot armature DC motor and 10 -slot armature DC motor.

Stereo vision with 3D coordinates for robot arm application guide

This paper presented the application of stereo vision system for robot arm guidance application. The stereo vision system comprises the process of camera calibration, image rectification, stereo correspondences and 3D reconstruction. Camera calibration process was carried out to permit the extraction of camera intrinsic and extrinsic parameters for the image rectification purposes. Next, the image rectification process will transform and align the images such that corresponding features in each image will appear on the same row. Then, stereo correspondences were performed using the method of Sum of Differences (SAD) block matching algorithm. Lastly, the 3D reconstruction was implemented by backprojecting the image pixel in 3D point. From the experimental results, the stereo vision system well performed as the correct shape of the object and the depth of the stereo scene are recovered. The location and the distance of the object can be obtained through the 3D point.

Stereo matching algorithm for 3D surface reconstruction based on triangulation principle

This article presents a new stereo matching algorithm based on local method. The absolute difference (AD) algorithm works fast and precise at low texture area, however this algorithm is sensitive to radiometric distortions (i.e., contrast or brightness) and low texture areas. To overcome these problems, the proposed algorithm utilizes a combination of AD, gradient difference (GM) and census transform (CT). The GM algorithm is robust against the radiometric errors and CT algorithm works well on the low texture regions. The proposed algorithm performs much better based on the experimental results of the Middlebury dataset. The disparity map from the result consists of depth information which requires for the three-dimensional (3D) surface reconstruction.

Design and control of a multi-mode drive system

A structure of a drive system is presented which allows operation in a number of modes, which may be combined in various ways to give optimum performance for a given motion. The drive mode is controlled by a number of clutches and brakes and the drive also includes a spring which can be used to store energy under the control of the clutches. In one operating mode this spring is used to repeatedly transfer packets of energy from the input to the load in such a way that a variable speed ratio is achieved. In a second mode the spring is used to store energy extracted from the load at the end of one operation to be used at the beginning of a subsequent motion. Other modes allow precise position control and load braking. The paper describes the operating modes and control strategies and presents results for a prototype device.

A Laplacian based image filtering using switching noise detector

This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction of the pixels value with their related Laplacian value weighted by local noise estimator. The only parameter which controls smoothness is the number of iterations. Noise reduction quality of the introduced method is evaluated and compared with some classic algorithms like Wiener and Total Variation based filters for Gaussian noise. And also the method compared with the state-of-the-art method BM3D for some images. The algorithm appears to be easy, fast and comparable with many classic denoising algorithms for Gaussian noise.

Design and testing of a dual-mode mechanical drive

A dual-mode mechanical drive is designed to allow operation in two modes, which may be combined in various ways to give optimum performance for a given motion such as high speed movement, high acceleration and high accuracy for point-to-point movement. The operations are controlled by a number of clutches and a brake. The drive also consists of a spring which can be used to repeatedly transfer packets of energy from the input to the load in such a way that a variable speed ratio is achieved. The dual-mode drive concept was investigated by the development of a prototype which is controlled from a PC through two interfacing cards and a number of drivers and sensors. The performance of the built prototype was analysed and compared with simulation. The drive system proves that it can be useful for high performance applications.

An edge detection based noise removal algorithm

Abstract We present an image denoising method using the edge map of an image. The denoised image is considered as a linear combination of the observed image and its average value, where the coefficients are controlled by a local edge detector. The parameters are set on suitable values related to noise energy computed by the curvature norm of the original image. Implementation can be done in a single iteration and the speed of the process is reasonably high. Noise reduction quality of the introduced method is compared with Wiener and Total Variation based filters for some images. The method appears to be easy, fast and useful for very noisy images. The differences between our method and the patent 6229578 “Edge Detection Based Noise Removal Algorithm” are explained.

Power management for USB2.0 5V supply using load resistive and switch capacitive detection approach

In this paper, two proposed power management circuitries for USB 5V supply are demonstrated by using the current sense amplifier and switches architecture. The design architecture was simulated by using the LTspice tools. There are some power losses in the switched-mode power supply (SMPS) when supplying 5V to the USB port in board level design. The Cedar board will be used as a reference board throughout this work. The total amount of losses in Cedar 5V SMPS is measured and calculated which consumes 21mW. Two proposed detection circuitries which are load resistive and switch capacitive are used to save the power losses in SMPS. The simulation results for the power consumption of load resistive approach consume 2mW whereas for switch capacitive approach consumes 7.5mW when the 5V SMPS is switched off. The results show that the load resistive and switch capacitive approaches will save total amount of 19mW and 13.5mW respectively in the Cedar board design. The load resistive approach has been implemented using breadboard and printed circuit board (PCB) and the power consumption when the 5V SMPS is switched off is measured which consumes 2.536mW. The total power saving is 18.5mW. The performance of this design is optimum for USB2.0 current from 10mA to 200mA for achieving the low power purpose.