Articles in This Issue
Abstract
In this paper a fully neural network-based structure have been proposed to control speeds of rolling stands of a steel rolling mill. The structure has property of controlling the motors speed such that the loop height between each successive stands tracks the required height reference. Synchronization between these stands is also maintained so that the metal flow rate from first stand to the last stand is kept constant. This structure is robust against the disturbance effects such as, torque loading, plant parameter change... etc. The results reveal performance of the structure as a comparison with the conventional control method for a practical worksheet data.
Abstract
In this paper, an Industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (IC) Chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from Texas Instrument is used in the investigation. The inspection has to identify the print errors such as illegible character, missing characters and up side down printing. The vision inspection of the printed markings on the IC chip is carried out in three phases namely image preprocessing, feature extraction and classification. Projection profile and Moments are employed for feature extraction. A neural network is used as a classifier to detect the defectively marked IC chips. Both feature extraction methods are compared in terms of marking inspection time.
Abstract
In this paper a neurofuzzy control structure is presented and used for controlling the two-link robot manipulator. A neurofuzzy networks are constructed for both the controller and for identification model of robot manipulator. The performance of the proposed structure is studied by simulation. Different operating conditions are considered. Results of simulation show good performance for the proposed control structure.
Abstract
This paper presents and discusses a buck DC/DC converter control based on fuzzy logic approach, in which the fuzzy controller has been driven by voltage error signal and a current error signal for which the load current has been taken as a reference one. The validity of the proposed approach has been examined through starting the buck DC/DC converter at different loading and input voltages (to monitor the starting performances), exposing the converter into large load resistance and input voltage step variations (to explore its dynamic performance), in addition to step and smooth variation in the reference voltage (to see its ability in readjusting its operating point to comply with the new setting). The simulation results presented an excellent load & line regulations abilities in addition to a good reference tracking ability. It also showed the possibility of using the buck converter as smooth variable voltage source (under smooth reference voltage variations).
Abstract
In this paper, a fuzzy based controller for boost type AC/DC converter has been presented. Its operation and performance have been investigated through its simulation in the environment of Mat Lab. The system has been tested under various loading conditions. The obtained results showed that this fuzzy based controller can effectively control the power factor and the harmonic contents of the current drawn from the power factor system distribution network.
Abstract
This paper presents a proposed configuration of paralleling scheme PWM DC/DC buck converter. The topological structure and operation principles are presented. A Bode plot diagram technique is used to study the stability of the scheme for different values of controller parameters and with a number of parallel modules. It is found that the results are confidence, and the proposed scheme can be used in high power applications by increasing the number of parallel modules.
Abstract
Use of multilevel inverters is becoming popular in the recent years for high power applications. The important feature of these inverters is of having low harmonics content in the output voltage. The switching angles in a multilevel inverter are computed so as to produce an ac output voltage with minimum harmonics. A new control circuit is designed to achieve these angles. This control circuit has the ability to control the RMS output voltage using sinusoidal pulse width modulation (SPWM). The results presented in this work prove the ability of the designed control circuit to gain the required ac output voltage with minimum distortion.
Abstract
This paper proposes a new control circuit to control the switching of the main switches of the used Zero Current Zero Voltage Transition (ZCZVT) inverter to ensure Zero Current and Zero Voltage Switching (ZCZVS). The reverse recovery losses of the main diodes are minimized and the auxiliary switches of the commutation cell are turned on at Zero Current Switching (ZCS) and off at ZCZVS. The commutation losses are practically reduced to zero due to ZCS. Sinusoidal Pulse Width Modulation (SPWM) is used to perform the switching of the power semiconductor devices and to control the output voltage value. MATLAB software is used to simulate the inverter circuit. Simulation results are presented to demonstrate the feasibility of the proposed control circuit.
Abstract
In this study, the chaotic dynamics observed from a vertical cavity surface emitting lasers (VCSELS) subject to delayed optoelectronic feedback are investigated. The theoretical investigation is performed by using a MATLAB software package. The nonlinear dynamics of a VCSEL are examined using a single mode rate equations model. The key role played by system parameters such as delay time and the feedback strength on laser chaotic dynamics is addressed.
Abstract
This paper deals with NeuroFuzzy System (NFS), which is used for fingerprint identification to determine a person's identity. Each fingerprint is represented by 8 bits/pixel grayscale image acquired by a scanner device. Many operations are performed on input image to present it on NFS, this operations are: image enhancement from noisy or distorted fingerprint image input and scaling the image to a suitable size presenting the maximum value for the pixel in grayscale image which represent the inputs for the NFS. For the NFS, it is trained on a set of fingerprints and tested on another set of fingerprints to illustrate its efficiency in identifying new fingerprints. The results proved that the NFS is an effective and simple method, but there are many factors that affect the efficiency of NFS learning and it has been noticed that the changing one of this factors affects the NFS results. These affecting factors are: number of training samples for each person, type and number of membership functions, and the type of fingerprint image that used.