DC Motor with Load Coupled by Gears Speed Control using Modified Ziegler-Nichols Based PID Tunings

The used of DC motor in various applications has been increased due to the ease with which it speed can be controlled to give the desired performance characteristics under various condition. PID controllers are widely used in DC motor speed control due to its simple structure and robustness to the modeling error, however their effectiveness is often limited due to the poor selection (or tuning) of its parameters. To facilitate the determination of the appropriate values of the parameters of the PID controller for the control of DC motor at any set point therefore required using appropriate tuning method. This paper provides a better understanding of how PID controller is tuned using Ziegler-Nichols Step Response, Cohen-Coon Method and Chien–Hrones–Reswick (CHR) method. Experimental results of PID control of DC motor with load coupled by gear shows that CHR-PID tunings gives a much improved performance over Ziegler-Nichols Step Response and Cohen-Coon PID-tuning with settling time of 355sec., 112sec., and 111 sec . respectively at each set point Keywords: DC motor, Ziegler-Nichols Step Response, Cohen-Coon method and CHR metho

Voltage Stability Assessment Using Modal Analysis

Voltage instability incidence has of recent been a major threat to the optimum operation of a modern power system due to continuous increase in load demand and insufficient reactive power to meet the demand. Thus, it becomes imperative to carry out voltage stability assessment in a power system to prevent the catastrophe of voltage collapse. This work present voltage stability assessment using a technique based on modal analysis of the reduced Jacobian. The modal analysis method makes use of the power system Jacobian matrix to find the eigenvalues essential for the evaluation of the voltage stability of a power system. The bus with the smallest value of eigenvalue is taken as the critical mode of the system. The participation factor (PF) of each load node is then determined to evaluate the bus which contributes most to the critical mode identified. The bus with the highest value of PF is taken as the critical bus of the system. The effectiveness of the methodology presented is tested on the IEEE 30 bus power system. Result obtained shows that voltage stability assessment using modal analysis method could be of a great importance to power system operators in the identification of critical nodes that are liable to voltage collapse in power system. Keywords: Power flow, modal analysis, power system, voltage stability, participation facto

Comparative Study of a Fuzzy Logic Based Controller and a Neuro-Fuzzy logic Based Controller for Computer Fan

The impact of soft-computing in modern day engineering and technology cannot be overemphasized.  Fuzzy logic approach as proposed by Lofti Asker Zadeh, popularized by the Japanese, has found its way into the control of many domestic and industrial appliances/machines.  Unlike the popular PID controllers and the pulse width modulation based controllers, the performance of computer fan is investigated using the fuzzy logic approach with two inputs parameters, that is, the computer loads and the temperature and one output parameter which is the speed at which the computer fan operates.  For the fuzzy inference system, four membership functions are selected for the inputs as well as the output.  Relevant rules are set to determine the operating conditions and boundaries for the controller.  In order to make the controller adaptive, neurofuzzy logic appproach is used with parameters set as the case with fuzzy logic. Training of the controller is carried out and the performance of each controller is presented in three dimensional view and two dimensional surface view with neurofuzzy based controller, in performance, having an edge over the fuzzy logic based controller. Keywords: Anfis, Fuzzy logic, Computer fan, Controller, Performance compariso

APPLICATION OF FUZZY-MLP MODEL TO ULTRASONIC LIVER IMAGE CLASSIFICATION

In this paper, we propose the application of fuzzy-MLP in theclassification of ultrasonic liver images. The four sets of ultrasonic liverimages used in the experiment are: normal, liver cysts, alcoholic cirrhosisand carcinoma.To deal with the sample images efficiently, we extract textural features fromthe Pathology Bearing Regions (PBRs) of the ultrasound liver images. Theselected features for the classification are entropy, energy and maximumprobability-based texture features extracted using gray level co-occurrencematrix second-order statistics. The fuzzy-MLP model is constructed for theselected features classify various categories of ultrasonic liver images.The efficacy of Fuzzy-MLP model and conventional artificial neural network(ANN) has been compared on the basis of the same feature vector. A testwith 82 training data and 110 test data for all the four classes shows 92.73%classification accuracy for the proposed fuzzy-MLP model. It is comparedwith the 81.82% counterpart provided by conventional ANN method

Comparative of Ziegler Nichols, Fuzzy Logic and Extremum Seeking Based Proportional Integral Derivative Controller for Quadcopter Unmanned Aerial Vehicle Stability Control

Unmanned aerial vehicle is potentially recognized in autonomous sectors where intelligence gathering, surveillance, reconnaissance missions, power line inspection, aerial video, search and rescue monitoring devices are required. It is essential in modern era control and monitoring especially a rotary unit where quadcopter performed a crucial task. However, the flight behavior of a quadcopter is determined by the synchronous speed of each of the motors as the speed changes with load torque variations. The dynamics model equation of the system, external disturbances and its parameters variation of the motor makes it difficult for the manual tuning techniques employed into the system to perform its stability operation. The purpose of this work is to employ adaptive controllers to enhance the stability performance so as to prevent the risk of human lives and financial implication that may arise from improper monitoring of the system. Therefore, Ziegler Nichols, fuzzy logic and extremum seeking controllers were employed to auto-tuned the parameters of proportional integral derivative (PID) gains controller to optimize and give a satisfactory performance of motor speed control at different operating condition. The altitude, pitch, roll and yaw parameters of the quadcopter are simulated using the x-plane II flight simulator MATLAB tools. The simulation results presented in this work show better performance for extremum seeking-PID in terms of decrease in rise time, settling time and overshoot relative to Zigler-Nichols-PID and Fuzzy-PID controllers

Comparative Effect of Distance Metrics on Selected Texture Features for Content-Based Image Retrieval System

The effect of distance metrics on the retrieval performance of CBIR system characterized by texture features was evaluated in this paper. Tamura and Gabor Wavelet transform texture features were used to create the feature vector database and to match 4 sample query images respectively with the image database of 400 and 600 images of four different classes Euclidean distance, Manhattan distance, Cosine angle distance, Quadratic-form distance and Pearson correlation were used. The retrieval performance was evaluated using the average precision with the distance measures. Evaluated results from the CBIR system algorithm shows that Manhattan distance metric gave the best retrieval performance on the used two set of image database. Keywords: Content-Based Image Retrieval, Feature extraction, Distance metric

Modified one-class support vector machine for content-based image retrieval with relevance feedback

Image retrieval via traditional Content-Based Image Retrieval (CBIR) often incurs the semantic gap problem—non-correlation of image retrieval results with human semantic interpretation of images. In this paper, Relevance Feedback (RF) mechanism was incorporated into a traditional Query by Visual Example CBIR (QVER) system. The inherent curse of dimensionality associated with RF mechanism was catered for by performing feature selection using Principal Component Analysis (PCA). The amount of feature dimension retained was determined based on a not more than 5% loss constrain imposed on average precision of retrieval result. While the asymmetry and small sample size nature of the resultant image dataset informed the use of a modified One-Class Support Vector Machine (OC-SVM) classifier, three image databases (DB10, DB20 and DB100) were used to test the OC-SVM RF mechanism. Across DB10, DB20 and DB100, Average Indexing Time of 0.451, 0.3017, and 0.0904s were recorded, respectively. For a critical recall value of 0.3, precision values for QVER were 0.7881, 0.7200 and 0.9112, while OC-SVM RF yielded precision of 0.8908, 0.8409, and 0.9503, respectively. Also, the use of PCA yielded tolerable degradation of 3.54, 4.39 and 7.40% in precision on DB10, DB20, and DB100, respectively, with 80% reduction in feature dimension. The OC-SVM RF increased the precision and invariably the reliability of the CBIR system by ranking most of the relevant images higher. Also, the target class was identified faster than the conventional method, thereby reducing the image retrieval time of the OC-SVM RF