Mukhtiar Ali Unar

Zubair Ahmed Memon, Mohammad Aslam Uquaili, Mukhtiar Ali Unar

With the development of modern industrial technology a large number of non-linear loads are used in power system, which causes harmonic distortion in the power system. At the same time the power quality and safe operation becomes inferior. Therefore mitigation of harmonics is very necessary under the situation. This paper presents the design of two passive filters to reduce the current harmonics produced by nonlinear loads in industrial power system. Matlab /simulink software has been used for the simulation purpose. The results have been obtained with and without installation of filters and then it is observed that after installation of filters harmonics of the current are reduced and power factor is improved.

Zubair Ahmed Memon, Mohammad Aslam Uqaili, Mukhtiar Ali Unar

Power quality standards (IEEE-519) require to limit the total harmonic distortion within satisfactory range caused by power electronic based devices. Our work deals with the design of hybrid active filter to reduce current perturbations produced by power electronics based devices. The Instantaneous Active and Reactive Power Method (pq) is used to perform the identification of disturbing currents. The pq algorithm creates a reference current, whereas, this reference current is tracked by the current of the voltage source converter. The currents of the voltage source converter are controlled by hysteresis controller. Simulation results showed that the hybrid active filter can compensate the harmonic currents effectively and improve power quality.

Zeeshan Ali Memon, Mukhtiar Ali Unar, Dur Muhammad Pathan

MPC (Model Predictive Control) techniques, with constraints, are applied to a nonlinear vehicle model for the development of an ACC (Adaptive Cruise Control) system for transitional manoeuvres. The dynamic model of the vehicle is developed in the continuous-time domain and captures the real dynamics of the sub-vehicle models for steady-state and transient operations. A parametric study for the MPC method is conducted to analyse the response of the ACC vehicle for critical manoeuvres. The simulation results show the significant sensitivity of the response of the vehicle model with ACC to controller parameter and comparisons are made with a previous study. Furthermore, the approach adopted in this work is believed to reflect the control actions taken by a real vehicle.

Dur Muhammad Pathan, Mukhtiar Ali Unar, Zeeshan Ali Memon

This paper proposes a fuzzy logic controller for design of autopilot of a ship. Triangular membership functions have been use for fuzzification and the centroid method for defuzzification. A nonlinear mathematical model of an oil tanker has been considered whose parameters vary with the depth of water. The performance of proposed controller has been tested under both course changing and trajectory keeping mode of operations. It has been demonstrated that the performance is robust in shallow as well as deep waters.

Saba Baloch, Javed Ali Baloch, Mukhtiar Ali Unar

In most digital communication systems, bandwidth limited channel along with multipath propagation causes ISI (Inter Symbol Interference) to occur. This phenomenon causes distortion of the given transmitted symbol due to other transmitted symbols. With the help of equalization ISI can be reduced. This paper presents a solution to the ISI problem by performing blind equalization using ANN (Artificial Neural Networks). The simulated network is a multilayer feedforward Perceptron ANN, which has been trained by utilizing the error back-propagation algorithm. The weights of the network are updated in accordance with training of the network. This paper presents a very effective method for blind channel equalization, being more efficient than the pre-existing algorithms. The obtained results show a visible reduction in the noise content.

Muhammad Saleh Shah, Asim Imdad Wagan, Mukhtiar Ali Unar

Recent years have seen an increasing interest in the design of AQM (Active Queue Management) controllers. The purpose of these controllers is to manage the network congestion under varying loads, link delays and bandwidth. In this paper, a new AQM controller is proposed which is trained by using the SVM (Support Vector Machine) with the RBF (Radial Basis Function) kernal. The proposed controller is called the support vector based AQM (SAM) controller. The performance of the proposed controller has been compared with three conventional AQM controllers, namely the Random Early Detection, Blue and Proportional Plus Integral Controller. The preliminary simulation studies show that the performance of the proposed controller is comparable to the conventional controllers. However, the proposed controller is more efficient in controlling the queue size than the conventional controllers.

Niaz Ahmed Memon, Mukhtiar Ali Unar, Abdul Khalique Ansari

In this research, feedforward ANN (Artificial Neural Network) model is developed and validated for predicting the pH at 10 different locations of the distribution system of drinking water of Hyderabad city. The developed model is MLP (Multilayer Perceptron) with back propagation algorithm.The data for the training and testing of the model are collected through an experimental analysis on weekly basis in a routine examination for maintaining the quality of drinking water in the city. 17 parameters are taken into consideration including pH. These all parameters are taken as input variables for the model and then pH is predicted for 03 phases;raw water of river Indus,treated water in the treatment plants and then treated water in the distribution system of drinking water. The training and testing results of this model reveal that MLP neural networks are exceedingly extrapolative for predicting the pH of river water, untreated and treated water at all locations of the distribution system of drinking water of Hyderabad city. The optimum input and output weights are generated with minimum MSE (Mean Square Error) < 5%.Experimental, predicted and tested values of pH are plotted and the effectiveness of the model is determined by calculating the coefficient of correlation (R2=0.999) of trained and tested results.

Farida Memon, Mukhtiar Ali Unar, Sheeraz Memon

This paper presents the performance evaluation of eight focus measure operators namely Image CURV (Curvature), GRAE (Gradient Energy), HISE (Histogram Entropy), LAPM (Modified Laplacian), LAPV (Variance of Laplacian), LAPD (Diagonal Laplacian), LAP3 (Laplacian in 3D Window) and WAVS (Sum of Wavelet Coefficients). Statistical matrics such as MSE (Mean Squared Error), PNSR (Peak Signal to Noise Ratio), SC (Structural Content), NCC (Normalized Cross Correlation), MD (Maximum Difference) and NAE (Normalized Absolute Error) are used to evaluate stated focus measures in this research. . FR (Full Reference) method of the image quality assessment is utilized in this paper. Results indicate that LAPD method is comparatively better than other seven focus operators at typical imaging conditions.