Journal of Mechatronics, Electrical Power, and Vehicular Technology
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258 research outputs found
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A Modified Gain Schedulling Controller by Considering the Sparseness Property of UAV Quadrotors
No full textThis work presented the gain scheduling based LQR for Quadrotor systems. From the original nonlinear model, the system is always controllable and observable in various equilibrium points. Moreover, the linearized systems have a unique property that is known as sparse system. Hence, in order to implement the most efficient state feedback controller, post-filter and pre-filter were introduced to transform the state coordinate to decrease coupling between states. Finally, the gain scheduling systems using these facts was proposed. The system behavior was tested using the proposed controller. The numerical studies showed the effectiveness of the controller to achieve desired altitude, attitude, and its ability during the disturbanc
Geometry Analysis and Effect of Turbulence Model on the Radial Rotor Turbo-Expander Design for Small Organic Rankine Cycle System
No full textOrganic Rankine Cycle (ORC) is one of the most promising technology for small electric power generations. The geometry analysis and the effect of turbulence model on the radial turbo-expanders design for small ORC power generation systems were discussed in this paper. The rotor blades and performance were calculated using several working fluids such as R134a, R143a, R245fa, n-Pentane, and R123. Subsequently, a numerical study was carried out in the fluid flow area with R134a and R123 as the working fluids. Analyses were performed using Computational Fluid Dynamics (CFD) ANSYS Multiphysics on two real gas models, with the k-epsilon and SST (shear stress transport) turbulence models. The result shows the distribution of Mach number, pressure, velocity and temperature along the rotor blade of the radial turbo-expanders and estimation of performance at various operating conditions. The operating conditions are as follow: 250,000 grid mesh flow area, real gas model SST at steady state condition, 0.4 kg/s of mass flow rate, 15,000 rpm rotor speed, 5 bar inlet pressure, and 373K inlet temperature. By using those conditions, CFD analysis shows that the turbo-expander able to produce 6.7 kW and 5.5 kW of power when using R134a and R123, respectively
Development of a Fixed Wing Unmanned Aerial Vehicle (UAV) for Disaster Area Monitoring and Mapping
No full textThe development of remote sensing technology offers the ability to perform real-time delivery of aerial video and images. A precise disaster map allows a disaster management to be done quickly and accurately. This paper discusses how a fixed wing UAV can perform aerial monitoring and mapping of disaster area to produce a disaster map. This research was conducted using a flying wing, autopilot, digital camera, and data processing software. The research starts with determining the airframe and the avionic system then determine waypoints. The UAV flies according to the given waypoints while taking video and photo. The video is transmitted to the Ground Control Station (GCS) so that an operator in the ground can monitor the area condition in real time. After obtaining data, then it is processed to obtain a disaster map. The results of this research are: a fixed wing UAV that can monitor disaster area and send real-time video and photos, a GCS equipped with image processing software, and a mosaic map. This UAV used a flying wing that has 3 kg empty weight, 2.2 m wingspan, and can fly for 12-15 minutes. This UAV was also used for a mission at Parangtritis coast in the southern part of Yogyakarta with flight altitude of 150 m, average speed of 15 m/s, and length of way point of around 5 km in around 6 minutes. A mosaic map with area of around 300 m x 1500 m was also obtained. Interpretation of the mosaic led to some conclusions including: lack of evacuation routes, residential area which faces high risk of tsunami, and lack of green zone around the shore line
Development of a Microcontroller-based Wireless Accelerometer for Kinematic Analysis
No full textWireless sensor networks (WSNs) allow real-time measurement and monitoring with less complexity and more efficient in terms of obtaining data when the subject is in motion. It eliminates the limitations introduced by wired connections between the sensors and the central processing unit. Although wireless technology is widely used around the world, not much has been applied for education. Through VISSER, a low cost WSN using nRF24L01+ RF transceiver that is developed to observe and analyze the kinematics of a moving object is discussed in this paper. Data acquisition and transmission is realized with the use of a low power and low cost microcontroller ATtiny85 that obtains data from the ADXL345 three-axis accelerometer. An ATtiny85 also controls the receiving module with a UART connection to the computer. Data gathered are then processed in an open-source programming language to determine properties of an object’s motion such as pitch and roll (tilt), acceleration and displacement. This paper discusses the application of the developed WSN for the kinematics analysis of a toy car moving on flat and inclined surfaces along the three axes. The developed system can be used in various motion detection and other kinematics applications, as well as physics laboratory activities for educational purposes
Comparative Study Between Internal Ohmic Resistance and Capacity for Battery State of Health Estimation
No full textIn order to avoid battery failure, a battery management system (BMS) is necessary. Battery state of charge (SOC) and state of health (SOH) are part of information provided by a BMS. This research analyzes methods to estimate SOH based lithium polymer battery on change of its internal resistance and its capacity. Recursive least square (RLS) algorithm was used to estimate internal ohmic resistance while coloumb counting was used to predict the change in the battery capacity. For the estimation algorithm, the battery terminal voltage and current are set as the input variables. Some tests including static capacity test, pulse test, pulse variation test and before charge-discharge test have been conducted to obtain the required data. After comparing the two methods, the obtained results show that SOH estimation based on coloumb counting provides better accuracy than SOH estimation based on internal ohmic resistance. However, the SOH estimation based on internal ohmic resistance is faster and more reliable for real applicatio
An Experiment of Ocular Artifacts Elimination from EEG Signals using ICA and PCA Methods
No full textIn the modern world of automation, biological signals, especially Electroencephalogram (EEG) is gaining wide attention as a source of biometric information. Eye-blinks and movement of the eyeballs produce electrical signals (contaminate the EEG signals) that are collectively known as ocular artifacts. These noise signals are required to be separated from the EEG signals to obtain the accurate results. This paper reports an experiment of ocular artifacts elimination from EEG signal using blind source separation algorithm based on independent component analysis and principal component analysis. EEG signals are recorded on three conditions, which are normal conditions, closed eyes, and blinked eyes. After processing, the dominant frequency of EEG signals in the range of 12-14 Hz either on normal, closed, and blinked eyes conditions is obtained.
Learning Efficiency of Consciousness System for Robot Using Artificial Neural Network
No full textThis paper presents learning efficiency of a consciousness system for robot using artificial neural network. The proposed conscious system consists of reason system, feeling system and association system. The three systems are modeled using Module of Nerves for Advanced Dynamics (ModNAD). Artificial neural network of the type of supervised learning with the back propagation is used to train the ModNAD. The reason system imitates behaviour and represents self-condition and other-condition. The feeling system represents sensation and emotion. The association system represents behaviour of self and determines whether self is comfortable or not. A robot is asked to perform cognition and tasks using the consciousness system. Learning converges to about 0.01 within about 900 orders for imitation, pain, solitude and the association modules. It converges to about 0.01 within about 400 orders for the comfort and discomfort modules. It can be concluded that learning in the ModNAD completed after a relatively small number of times because the learning efficiency of the ModNAD artificial neural network is good. The results also show that each ModNAD has a function to imitate and cognize emotion. The consciousness system presented in this paper may be considered as a fundamental step for developing a robot having consciousness and feelings similar to humans
