28 research outputs found
Vision System for Autonomous Underwater Vehicle Using Wireless Camera for Monitoring and Surveillances Application
This paper present the new design of vision system for autonomous underwater vehicle with the implementation of wireless camera, whereby, produce clearer image. The major obstacle faced by underwater vision system is the extreme loss of color and contrast when submerged to any significant depth whereby the image quality produced is low. Therefore, as to obtain clearer images, several investigations will be done in order to know the appropriate distance required between the images with the camera. At the end of the project, the new design of the vision system will be well functioned and can be applied to capture clearly the underwater images and also might be used to explore the nature of underwater. This new vision system also could be used for monitoring, surveillances, and maintenance tasks for underwater where it is risky for the human to work in it
Obstacle Avoidance System for Unmanned Underwater Vehicle using Fin System
An underwater glider is a type of an unmanned underwater vehicle (UUV). The movement of an underwater glider in the water is based on the buoyancy-propelled for float and fixed-winged for stabilizing the glider’s body. However, a
fixed wing underwater glider has limitation to avoid hitting the obstacle in front of it. To overcome this problem, the application of fin system in underwater glider is needed. In this project, a methodology was introduced which is design a flexible fin system of an underwater glider for obstacle avoidance purpose. This project mainly focused on SolidWorks’s simulation and analysis of -30°, -45°, -60° for submerge and rise up at 30°, 45°, 60° to get the most suitable angle for the glider’s fin system to submerge and rise up. The UTeM underwater glider is modified from fixed to flexible wing. Hence, Peripheral Interface Controller (PIC) is used to program the movement of the glider’s wings for upward at 45°and downward at -45°in the water. Thus,a flexible fin system for obstacle avoidance is designed and applied in UTeM underwater glider
Development and Modeling of Water Tank System using System Identification Method
This paper presents the development and modeling of Water Tank System (WTS) for temperature control using system identification technique. The WTS consists of the tank with
30 liter water, a stirrer, heater and thermocouple was powered by 240VDC and the system run by LabView software. The stirrer used to stabilize the water temperature that installed on the top cover of the WTS. In this project, a prototype of the WTS will be developed first. The WTS will be tested on an open loop system to obtain measured input-output signals. Input and output signals from the system are recorded and analyzed to infer a model. Then, system identification toolbox in MATLAB will be applied to generate a model of the WTS. The experimental testing of WTS
only considered in temperature control. The modeling obtained will be used to design the a suitable controller for temperature control. The most crucial issue is the control system. It is needed for the WTS to perform the desired temperature setting. The objective of this project is to reduce or eliminate the overshoot of system response from temperature setting. The conventional controller PID and Fuzzy Logic Controller (FLC) will be used to control the temperature so that the temperature will maintain its
desired temperature. The result shows that FLC is the better
performance of system response in term of overshoot and
oscillation
Synchronization of Compass Module with Pressure and Temperature Sensor System for Autonomous Underwater Vehicle (AUV)
This paper describes the synchronization of compass module with pressure and temperature sensor system for an Autonomous Underwater Vehicle (AUV). In general this project is the result of a combination of existing technology for underwater sensory to produce a complete system that aims to identify the position of the AUVs based on AUV degree of freedom. This can be done with the help of compass module that can find and order the AUV is moving at a fixed angle. This created a system that aims to obtain data on pressure and temperature in the AUV. Not only that, the project also aims to prove that the relationship between pressure and depth of the water and the relationship between pressure and temperature. All data gathered is capable of helping in the preparation of an AUV that can accommodate high pressure according to the depth to destination
Synchronization of Compass Module with Pressure and Temperature Sensor System for Autonomous Underwater Vehicle (AUV)
This paper describes the synchronization of compass module with pressure and temperature sensor system for an Autonomous Underwater Vehicle (AUV). In general this project is the result of a combination of existing technology for underwater sensory to produce a complete system that aims to identify the position of the AUVs based on AUV degree of freedom. This can be done with the help of compass module that can find and order the AUV is moving at a fixed angle. This created a system that aims to obtain data on pressure and temperature in the AUV. Not only that, the project also aims to prove that the relationship between pressure and depth of the water and the relationship between pressure and temperature. All data gathered is capable of helping in the preparation of an AUV that can accommodate high pressure according to the depth to destination
Analysis Movement of Unmanned Underwater Vehicle using the Inertial Measurement Unit
In an Unmanned Underwater Vehicle (UUV), the craft's orientation, velocity, and gravitational forces are the
important measurements to make sure the UUV’s navigation
system can be fully operated. Most of the current UUV system uses pressure sensor to control the navigation of the craft. But the pressure sensor is not suitable to use in getting UUV’s navigation data or information. Without the information on UUV’s navigation, there are difficult to monitor the movement of UUV. This project introduces a methodology to analyze the position, velocity vector and the rotation of UUV, using a combination of accelerometer and gyroscope. This sensing unit is a combination of Accelerometer ADXL-345 sensor and Gyroscope ITG-3200 sensor called as an Inertial Measurement Unit (IMU). The measurement unit will be programmed by an Atmel microcontroller (Arduino UNO) to get the important data of the UUV’s navigation system. The real-time data of sensing unit communicated with Serial Chart and Processing software to get output graph and real-time 3D animation of UUV. From this project outcome, the movement of UUV is monitored in processing software. Hence, the navigation system of a UUV such as auto depth control, left-right movement and obstacle avoidance purpose can be improved
Road Vehicle Following System With Adaptive Controller Gain Using Model Reference Adaptive Control Method Lyapunov Approaches
In order to maintain stability and satisfy operating constraints, the control system on the following vehicle needs information about the motion of preceding vehicle. A one-vehicle look-ahead control strategy is proposed and will be investigated for this operation. A mathematical model for this control strategy is obtained and simulated. This paper describes the process of designing an adaptive controller gain for a road vehicle following system using two Lyapunov approach. One approaches utilizes the perfect modelling while the other does not. This is done through simulations and comparisons and is further discussed to find the effectiveness of the two Lyapunov approaches
Performances Evaluation and Comparison of Two Algorithms for Fuzzy Logic Rice Cooking System (MATLAB Fuzzy Logic Toolbox and FuzzyTECH)
This paper presents an evaluation of performances rice cooking system with using Intelligent Controller that is Fuzzy Logic Controller (FLC) to meet the special requirements and some limitations of the rice cooking system. A new inference scheme is given to estimate the amount of rice and water to be used, and the temperature will be controlled according to the amount of rice and the time while cooking. The FLC system is designed by using two types of simulation software which are MATLAB Fuzzy Logic Toolbox and FuzzyTECH. The results obtained from the both simulation software are given in this paper. The differences the between both simulation also will be discussed. MATLAB Toolbox gives more specific results compared FuzzyTECHsoftware. The both software meet the special requirements because is not much differ between each other
Analysis of movement for unmanned underwater vehicle using a low cost integrated sensor
This paper presents the development of low cost integrated Smart Sensor for Unmanned Underwater Vehicle
(UUV) namely as underwater Remotely Operated Vehicle (ROV). In the underwater industries, the most crucial issues
are the sensors that are needed for the underwater task. The sensors that are utilized in this area are quite expensive and sensitive. Every sensors used in the underwater vehicle are not in the form of integrated sensors and most of them based on case to case basis. However, nowadays, a lot of industries are involved in the development of the integrated sensor in order to reduce the production cost as well as to increase accuracies, efficiencies and productivities. Therefore, this
research proposes an integrated sensor to be applied in the underwater operations. The integrated sensor is designed
based on three goal performances which are; the accuracies; the sensitivities and the cost efficiencies. This integrated
sensor is the combination of pressure sensor, inertial measurement unit (IMU), digital compass and temperature sensor that are placed in a waterproof casing. This integrated sensor is targeted to be used to control the movement of ROV to maintain its position called station keeping. The purpose of the station keeping is to ensure the ROV to remain stationary at the desired depth by utilizing the pressure sensor. The experimental studies have been carried out in order to see the responses of each sensor