Khalid Isa

Dynamic modeling and characteristics estimation for USM underwater glider

Underwater gliders are a new class of autonomous underwater vehicles, which are energy efficient, inexpensive and can be utilised for long duration mission. They use a ballast system and moving mass to glide in the saw-tooth path pattern through the ocean water column. This paper presents the dynamic model of USM underwater glider based on slender-body theory. In this work, a moving mass implementation and hydrodynamic interaction among hull, wings, and tail are included. The simulation results illustrate the dynamic characteristics and its response over velocity and angle of attack. In the results, the equilibrium angle of attack and velocity of underwater glider at minimum drag force can be obtained based on specific dimension. In this work, USM underwater glider produced minimum drag force at 1.7° angle of attack with velocity of 2.7 m/s. In addition, the effectiveness of a moving mass actuator also presented in the simulation results. This model will be used for further works in developing an optimized USM underwater glider with six degrees of freedom, including designing an establish full mathematical model of its motions and control algorithm.

An analysis of homeostatic motion control system for a hybrid-driven underwater glider

This paper presents an analysis of homeostatic controller, which controls the motion of a hybrid-driven underwater glider. The homeostatic controller is inspired from a biological process known as homeostasis, which maintains a stable state in the face of massively dynamics conditions. Within a biological context, organism homeostasis is an emergent property of the interactions between nervous, endocrine and immune system. Artificially these three systems are presented as Artificial Neural Network (ANN), Artificial Endocrine System (AES) and Artificial Immune System (AIS). The ANN is designed as the controller backbone, the AES is designed as the weight tuner, and the AIS is designed as the optimizer of the control system. The design objective is to obtain better control performance of the motion control system which includes the disturbance from the water currents. We have simulated the algorithm by using MatlabTM, and the results demonstrated that the homeostatic controller reduced the cost function of the control system and produced better control performance than the neuroendocrine controller.

Neural Network Control of Buoyancy-Driven Autonomous Underwater Glider

This chapter presents a mathematical model and motion control analysis of a buoyancy-driven underwater glider. The glider mathematical model, which includes the presence of disturbance from the water currents, has been designed by using the Newton-Euler method. In order to predict and control the glider motion, a neural network control has been used as a model predictive control (MPC) as well as a gain tuning algorithm. The motion has been controlled by six control inputs: two forces of a sliding mass, a ballast pumping rate, and three velocities of water currents. The simulation results show the analysis of the motion control system for both neural network control approaches, and a comparison with the Linear Quadratic Regulator (LQR) controller is also included. The results show that the model is stable, and the neural network controller of MPC produced better control performance than the neural network gain tuner and the LQR, where the accuracy value of the MPC is 94.5 %.

Motion simulation for propeller-driven USM underwater glider with controllable wings and rudder

This paper describes the dynamic model and motion simulation for propeller-driven USM underwater glider with independently controllable wings and rudder. The underwater glider is a highly efficient autonomous underwater vehicle which glides through the ocean water column in saw-tooth pattern. It uses buoyancy for propulsion by controlling ballast pump and internal moving mass. However, in our research work, we attempt to design an underwater glider which can be driven by buoyancy or propeller, and the external actuators (wings and rudder) can be controlled independently. We have designed the mathematical model and studied the dynamic characteristics of USM underwater glider. The simulation results demonstrate the motion of propeller-driven USM underwater glider based on different angles of wings and rudder. The results show the position of glider, linear and angular velocities of the glider, angle of attack and glider speed. With the resulting glider behavior in this open loop control output, we will extend the control approach in order to create an efficient biologically inspired control algorithm for an optimized hybrid-driven USM underwater glider.

Development of INPLANS: An analysis on Students’ Performance Using Neuro-Fuzzy

This paper presents a simulation of Neuro-Fuzzy application for analysing studentspsila performance based on their CPA and GPA. The analysis is an extension of our previous study, which was called an analysis on studentpsilas performance using fuzzy systems. The main function of this analysis is to support the development of intelligent planning system (INPLANS) using fuzzy systems, neural networks, and genetic algorithms which will be used by the academic advisory domain in educational institutions by evaluating and predicting studentspsila performance as well as comparing the results with the previous study. The neuro-fuzzy model is connectionist feed-forward architecture with five layers of neurons and four connections. The system has been tested for 26 cases of studentspsila results. The results show that the studentspsila performances have improved significantly compared to the prediction of the same case using fuzzy systems.

Unsupervised floating platform for environmental monitoring

Environmental monitoring plays an important role in human life, so this project aims to provide a spatial-temporal resolution of data collected inland water storages and lakes through the development of a unique floating platform. Several challenges in monitoring environment especially the accessibility to the site and representativesness of data cause the quality of water and air become worse. Hence, an unsupervised floating platform was developed in order to monitor the environment. The system focused on doing a precision measurement of water quality and air quality. With the help of several sensors that act as an input that is Real-Time Clock, Global Positioning System (GPS) sensor, humidity and temperature sensor, pH sensor and carbon monoxide sensor. Through this sensor, the floating platform collects the data and save it for every 10 minutes to perform real-time data collection. The data are saved into SD card, which consists of time, date, longitude, latitude, carbon monoxide, water pH value, temperature, and humidity. The results obtained then used to evaluate the quality of the air and water of the lake.

Silence removal from isolated Malay words using framing and windowing method

The most important domain in digital signal processing is speech signal processing. This is because a variety of noise signals could degrade the original speech signal and make it unclear to user. This project contributes to the literature by developing a program to remove silence from the original speech signal using framing and windowing method. Eight subjects from different gender and age have been asked to utter four Malay words and their voices are recorded to evaluate the effectiveness of the developed program. The results reveal that the program can be used effectively for removing silence.The most important domain in digital signal processing is speech signal processing. This is because a variety of noise signals could degrade the original speech signal and make it unclear to user. This project contributes to the literature by developing a program to remove silence from the original speech signal using framing and windowing method. Eight subjects from different gender and age have been asked to utter four Malay words and their voices are recorded to evaluate the effectiveness of the developed program. The results reveal that the program can be used effectively for removing silence.

Intelligent Agent Simulator in Massive Crowd

Received Mar 3, 2018 Revised Apr 11, 2018 Accepted Apr 21, 2018 Paintball has gained a huge popularity in Malaysia with growing number of tournaments organized nationwide. Currently, Ideal Pro Event, one of the paintball organizer found difficulties to pair a suitable opponent to against one another in a tournament. This is largely due to the manual matchmaking method that only randomly matches one team with another. Consequently, it is crucial to ensure a balanced tournament bracket where eventual winners and losers not facing one another in the very first round. This study proposes an intelligent matchmaking using Particle Swarm Optimization (PSO) and tournament management system for paintball organizers. PSO is a swarm intelligence algorithm that optimizes problems by gradually improving its current solutions, therefore countenancing the tournament bracket to be continually improved until the best is produced. Indirectly, through the development of the system, it is consider as an intelligence business idea since it able to save time and enhance the company productivity. This algorithm has been tested using 3 size of population; 100, 1000 and 10,000. As a result, the speed of convergence is consistent and has not been affected through big population.N. N. S. Abdul Rahman, N.M. Saad, A. R. Abdullah, M. R. M. Hassan, M. S. S. M. Basir, N. S. M. Noor 1,2,4,6Faculty of Electronic and Computer Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 2,3Center for Robotics and Industrial Automation, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 3,5Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MalaysiaLight rail transit (LRT), or fast tram is urban public transport using rolling stock similar to a tramway, but operating at a higher capacity, and often on an exclusive right-of-way. Indonesia as one of developing countries has been developed the LRT in two cities of Indonesia, Palembang and Jakarta. There are opinions toward the development of LRT, negative and positive opinions. To reveal the level of LRT development acceptance, this research uses machine learning approach to analyze the data which is gathered through social media. By conducting this paper, the data is modeled and classified in order to analyze the social sentiment towards the LRT development.Mohamad, S., Nasir, F.M., Sunar, M.S., Isa, K., Hanifa, R.M., Shah, S.M., Ribuan, M.N., Ahmad, A. 1,4,6,7,8Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 1,2,3UTM-IRDA Digital Media Centre, Media and Game Innovation Centre of Excellence, Universiti Teknologi Malaysia, Johor, Malaysia 1,2,3Faculty of Computing, Universiti Teknologi Malaysia, Johor, Malaysia 5Centre for Diploma Studies, Universiti Tun Hussein Onn Malaysia, Johor, Malaysia 6Research Centre for Applied Electromagnetics, Universiti Tun Hussein Onn Malaysia, Johor, MalaysiaReceived Jan 31, 2018 Revised Apr 21, 2018 Accepted Apr 30, 2018 Bluetooth is an emerging mobile ad-hoc network that accredits wireless communication to connect various short range devices. A single hop network called piconet is the basic communication topology of bluetooth which allows only eight active devices for communication among them seven are active slaves controlled by one master. Multiple piconets are interconnected through a common node, known as Relay, to form a massive network called as Scatternet. It is obvious that the performance of Scatternet scheduling is highly dependent and directly proportionate with the performance of the Relay node. In contrary, by reducing the number of Relays, it may lead to poor performance, since every Relay has to perform and support several piconet connections. The primary focus of this study is to observe the performance metrics that affects the inter-piconet scheduling since the Relay node’s role is like switch between multiple piconets. In this paper, we address and analyze the performance issues to be taken into consideration for efficient data flow in Scatternet based on Relay node.

Malay speech recognition for different ethnic speakers : An exploratory study

Speech technology has become an alternative medium of communication. It could help those on smart wheelchair to use their voice to ease their movements from one location to another. However, most of the speech technology that has been developed is based on the English language and limited for other languages. This project contributes to the literature by developing a program on speech technology for Malay speech recognition using Visual C# to determine the quality of the program in advancing the state-of-the-art. The developed program has been tested using the speech by 13 subjects from different ethnic backgrounds to evaluate its quality and limitations. Results indicate that the voice, including the volume, accent and word emphasis to be important elements in influencing the quality of recognition.

Speech semantic recognition: A control mechanism for assistive robot

Speech semantic recognition system is a system that can be applied on assistive robotic application that using a meaning of speech for people who suffers permanent disability to move around freely. In this project the user interface is provided in order to receive the speech input from the user and delivers the input of the speech from the user to the application. Speech signal is the input. From the speech signal, equivalent word can be identified. The word semantic model signifies the correlation between semantic databases that represent the meaning of a word with the registered word belonging to speech recognizer. The word that has been recognized then is converted to a matching word semantic model by using feature extraction approach. Later, the word that has been converted is stored in the database and trained. According to the feature matching method, the speech recognizer will recognize the speech signal again then the application will alerted thru comparing the word semantic model stored in the data before direct to the application interface. Since this system is successfully developed, this system also can be applied on Autonomous surface vehicle or unmanned surface vehicles (USV).