Informatics Publishing Limited

Muhammad Faisal ¹, Mohsin Jamil ¹, Qasim Awais ², Usman Rashid ¹, Muhammad Sami Syed Omer Gilani ¹, Yasar Ayaz ¹, Muhammad Nasir Khan ³

Affiliations
1 Department of Robotics and Artificial Intelligence, School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology, H-12 Main Campus, Islamabad, PK
2 University of Central Punjab, Lahore, PK
3 University of Lahore, PK

Abstract

In this paper, we have investigated the performance of Iterative Linear Quadratic Regulator (ILQR) on trolley position of 3DOF crane. In ILQR, we select optimum parameters Q and R automatically instead of hit and trial method. Algorithm chooses the parameters Q and R which results in minimum trolley’s settling time of the jib system. A number of simulations have carried out using Matlab/Simulink. The results show that the optimized LQR results reduce settling time of trolley along with smaller overshoot with less rise time.

Keywords

Iterative Linear Quadratic Regulator (ILQR), Proportional Integral Derivative (PID), Three Degree of Freedom (3DOF)

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Habib Ahmed ¹, Syed Omer Gilani ¹, Mohsin Jamil ¹, Yasar Ayaz ¹, Syed Irtiza Ali Shah ¹

Affiliations
1 School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), H-12 Main Campus, Islamabad, PK

Abstract

Background/Objectives: To construct a Pakistani sign language learning-based gesture recognition system with a reasonable rate of accuracy. Methods/Statistical Analysis: It should be <70 words. Include the method adapted to study the objectives/sampling details or simulation or statistical analysis of data; technique employed; mention unique/ important points of modification of methodology in the current study. Mention about test samples the control employed or approach used for comparing the test sample. Findings: The proposed system uses static images to extract local and global, region and boundary-based descriptors for acquiring gesture information, which is provided as input for supervised learning method known as Support Vector Machine (SVM). The purpose of this research is to formally introduce a practical learning-based PSL recognition system, which can lay the groundwork for future research pertaining to PSL. The proposed system was developed and the ten class supervised learning based system was able to achieve an accuracy of 83%. Application/Improvements: It is a preliminary work, which will be further improved to construct a real-time static and dynamic gesture based PSL system that is able to recognize words and sentences information.

Keywords

Fourier Descriptors, Gesture recognition, Hu Moments, Sign Language Recognition, Support Vector Machines.

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Shahab Shahid Khawaja ¹, Mohsin Jamil ¹, Qasim Awais ², Umer Asgher ¹, Yasar Ayaz ¹

Affiliations
1 Department of Robotics and Artificial Intelligence, School of Mechanical and Manufacturing Engineering, National University of Sciences and Technology, H-12 Main Campus, Islamabad, PK
2 University of Central Punjab, Lahore, PK

Abstract

With the depletion of fossil fuel, the world is shifting towards the sources of alternate energy, but a major impediment in their utilization is their inter-connection with the grid. This paper builds on the model of a grid-connected converter which is used to interface the different alternate energy sources using matlab/simulink as simulation software. The classical control techniques proportional/proportional integral (P/PI) are applied on the model of the two-level grid-connected converter with LCL filter. The overall structure of the system is based upon the inner-loop capacitor current and outerloop controller feedback. These parameters are varied and their effect is investigated in the presence of utility harmonics. The limitations and performance of the system with the variation in gain values is studied so that optimal gains can be identified.

Keywords

Grid-Connected Converters, Micro-grid, Total Harmonic Distortion

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