Indonesia Conference Directory

Corresponding Author
LEN Len

Institutions
LEN

Abstract
Field Oriented Control in PMSM needs accurate angle information to generate maximum torque and less ripple. However, many economic PMSM motors are only equipped with hall sensors which have up to 60 degrees error. In some applications where continuous torque is necessary, angle error will lead the motor into stall condition or even stopped rotating. A state observer is proposed to improve FOC control performance by reducing angle error from Hall sensors. Current and voltage input of the motor is used as information to predict the rotor angle. Computer simulation has been done using PSIM(TM), and the simulation result shows a significant improvement on the performance indicated by less torque ripple.

Keywords
Field Oriented Control

Topic
Control System

Link: https://ifory.id/abstract/brBKzn9v4hfw

Corresponding Author
Numan Amri Maliky

Institutions
Institut Teknologi Bandung

Abstract
While a barge is operating, there are hydrodynamics forces influencing motion of the barge. To create an autonomous barge, there are some parameters that must be obtained. There are many methods to generate data for these parameters, such as experiment and computational simulation. CFD method is the best way to obtain the parameters. Besides having a high level of accuracy, CFD method doesn-t require expensive cost compared to the experimental method.

Keywords
added mass, drag, control, autonomous, hydrodynamic, computational fluid dynamics, simulation, barge

Topic
Control System

Link: https://ifory.id/abstract/bqVBH4hfN2Qy

Corresponding Author
Tua A. Tamba

Institutions
National Center for Sustainable Transportation Technology (NCSTT), Bandung, Indonesia

Abstract
CBTC (communication-based train control) is a new train control technology which aims at managing a platoon of several trains to move simultaneously on a particular train segment through precise maintenance of a predetermined inter-train safe distance. The success of the CBTC technology implementation thus relies strongly on the availability of dedicated real-time communication systems which can accommodate the continuous data/information exchange/transmission among neighboring trains. With an objective of reducing both the computational effort and the communication network loads/traffics in such a CBTC implementation, this paper proposes a Lyapunov-based event-triggered control scheduling approach which can guarantee the input-to-state stability property of the closed loop CBTC system.

Keywords
CBTC, event triggering, input-to-state stability, Lyapunov method

Topic
Control System

Link: https://ifory.id/abstract/7rZFjuXaD4YH

Corresponding Author
Selvi Lukman

Institutions
Bandung Institute of Technology
Jalan Ganesha 10, Bandung 40132, Indonesia
State Key Laboratory of Rail Traffic,Control and Safety
Beijing Jiaotong University

Abstract
This paper presents the estimation of received power signal based on the Support Vector Regression (SVR). The simulated datasets are used, which contain the positions of transmitter (Tx) and receiver (Rx) , the distance between the TX and RX, and the corresponding path loss, and the carrier frequencies. SVR presents the accuracy estimation of simulated datasets computing which shows Mean Square Error (MSE) as the average value of estimation errors that are squared, Root Mean Square Error (RMSE) as another parameter for measuring the accuracy of a estimation as a root value of MSE Average Root also R² as the coefficient of determination tool for measuring how far the ability of the model in explaining some variations in the dependent variable. If the value of R² approaches one, it means that predictive results can follow variable patterns or variations well dependent. Cross Validation is a performance measurement .The aim is to find the best hyper-parameter combination so that machine learning can predict data accurately and prevent over-fitting problems. Optimal parameter values are determined by using the Grid Search Method, where machine learning will do modeling using the range C ɤ and ɛ given. Therefore, SVR Hyper-Parameter shows the most optimized parameter with C which affects the penalty given when there is an error in classification , Gamma that affects the pace of learning process, Epsilon indicates the error limit than can be ignored. The parameter values that produce the highest accuracy or the smallest error will be chosen as the best parameter.

Keywords
Estimation Machine Learning, Path Loss, Received Power Signal, SVR, 5G-R

Topic
Control System

Link: https://ifory.id/abstract/kqMA7tbR6cnm

Corresponding Author
Yul Yunazwin Nazaruddin

Institutions
Institut Teknologi Bandung

Abstract
Autonomous Vehicles is a system which can maneuver through its surrounding to reach a certain location and orientation. Path following control is one of the most proposed control scheme to achieve this objective. In this paper, the path following control, based on the Lyapunov stability approach, designed specifically for a bus, will be proposed and tested experimentally. The mathematical model of the bus kinematics and controller will be presented. The main concerns of the presentation will be the technical details of the path following control implementation such as the design of the system, the controller and actuator and also the data communication among all components. The experimental investigation was conducted using a miniature scaled bus with the length and width of the bus is 39 cm and 15.5 cm respectively. The communication protocol MQTT has been implemented for the data communication. The experimental results show how the bus followed the desired path satisfactorily.

Keywords
Autonomous vehicle, path following control, experimental design, Lyapunov stability

Topic
Control System

Link: https://ifory.id/abstract/DYaEWUhMTCFG

Corresponding Author
Muhamad Abdul Aziz

Institutions
Mechanical Engineering Department
Universitas Diponegoro
Semarang, Indonesia

National Center for Sustainable
Transportation Technology, Indonesia

Electrical Engineering Department
Universitas Diponegoro
Semarang, Indonesia

Faculty of Mechanical and Aerospace
Engineering
Institut Teknologi Bandung, Indonesia

Naval Architecture Department
Universitas Diponegoro
Semarang, Indonesia

Abstract
The autonomous boat in this research has the capability of using fully renewable energy sources in which its wing sail can provide aerodynamic forces for propulsion while the solar cells provide the power for control and communication systems. Thus, this boat can operate in a long duration, suitable for ocean research and monitoring missions. Similar to an airplane wing, the design of the wing sail is taken from NACA 0018 that can provide good performance in low Reynolds-number. The purpose of this study is to experimentally study the aerodynamic performance of a 1/4th scale wing sail by varying the flap angle in a laboratory set-up. The aerodynamic of wing sail produces lift and drag forces that depend on the wing sail angle of attack. In this study, an encoder is used to measure the angle of attack of wing sail, a potentiometer for measuring the flap angle, and an anemometer for measuring the wind speed. A servo motor is used for controlling the flap angle. The digital data acquisition uses Arduino Uno as the microcontroller which is wired to a PC and coded in MATLAB/Simulink using Arduino package. The experiment results show the wing sail performance, the effect varying flap angles. The total aerodynamic forces were generated in this experiment.

Keywords
Wing sail, wind propulsion, autonomous boat

Topic
Control System

Link: https://ifory.id/abstract/DX6QeLNFCbyj

Corresponding Author
Joga Dharma Setiawan

Institutions
Universitas Diponegoro

Abstract
The autonomous boat in this research has the capability of using fully renewable energy sources in which its wing sail can provide aerodynamic forces for propulsion while the solar cells provide the power for control and communication systems. Thus, this boat can operate in a long duration, suitable for ocean research and monitoring missions. Similar to an airplane wing, the design of the wing sail is taken from NACA 0018 that can provide good performance in low Reynolds-number. The purpose of this study is to experimentally study the aerodynamic performance of a 1/4th scale wing sail by varying the flap angle in a laboratory set-up. The aerodynamic of wing sail produces lift and drag forces that depend on the wing sail angle of attack. In this study, an encoder is used to measure the angle of attack of wing sail, a potentiometer for measuring the flap angle, and an anemometer for measuring the wind speed. A servo motor is used for controlling the flap angle. The digital data acquisition uses Arduino Uno as the microcontroller which is wired to a PC and coded in MATLAB/Simulink using Arduino package. The experiment results show the wing sail performance, the effect varying flap angles. The total aerodynamic forces were generated in this experiment.

Keywords
Wing sail, wind propulsion, autonomous boat

Topic
Control System

Link: https://ifory.id/abstract/udAgN3PyCW9D

Corresponding Author
Monika Faswia Fahmi

Institutions
Institut Teknologi Bandung

Abstract
Vehicle simulator is used for various purposes, mainly driver training and vehicle model test. One of the most important part of vehicle simulator is motion simulator which simulates the vehicle motion. This part makes the user feel the motion sensation given by the real vehicle even though the user is in the simulator platform. The motion simulator itself consists of several subsystems : user interface, dynamic model calculation, motion cueing, and platform control system. This paper explains the implementation and its result of designed motion cueing and the motor position control which is a part of platform control system. The design is implemented on vehicle simulator in Institut Teknologi Bandung which has 4 degrees of freedom for its motion (pitch, roll, sway, and surge). The implemented motion cueing algorithm (MCA) is model predictive control (MPC), an optimization-based motion cueing algorithm. Sliding mode control (SMC) with saturation function is implemented for position control of the motor to solve nonlinear load torque disturbance which appear from a static behaviour when the platform rotates on pitch motion. From the motion cueing result, it can be inferred that MPC-based MCA can track the motion sensation of the real vehicle, especially for the surge and sway motion. For pitch and roll sensation, reference signals with lower frequency yield worse results compared to the signals with higher frequency ones. Meanwhile, from the motor position control result, it can be concluded that SMC with saturation function can track the position reference according to the calculation of motion cueing.

Keywords
vehicle simulator, motion cueing, model predictive control, sliding mode control, nonlinear load torque

Topic
Control System

Link: https://ifory.id/abstract/Nh6HkrVLXBTb

Corresponding Author
Joshua Abel Oktavianus

Institutions
Department of Engineering Physics, Institut Teknologi Bandung. Jalan Ganesha no 10, Bandung 40132, Indonesia

Abstract
The combination of inertial measurement unit and global navigation satellite system is widely used in the localization of autonomous cars. However, global navigation satellite systems are highly dependent to the external conditions and have a low sampling rate. In order to make the localization of autonomous cars more reliable in various external condition, a virtual sensing system using Error State Kalman filter and Diagonal Recurrent Neural Network (DRNN) approach is proposed in this paper. In this proposed system, DRNN served as an estimator for the location of autonomous car. DRNN is applied due to its independency against external condition, the ability to learn, and also its faster sampling rate compared to global navigation system. Implementation and testing of this new approach using Carla Simulator shows that the proposed system could correct the deviation caused by the absence of absolute position measurement. By having this alternative sensing method, it is expected that it would be able to replace the existing global navigation satellite systems and unlock the possibility for offline localization.

Keywords
autonomous car, localization, virtual sensor, neural network, CARLA Simulator

Topic
Control System

Link: https://ifory.id/abstract/bYgWdqBHFm7P

Corresponding Author
Endra Joelianto

Institutions
Institut Teknologi Bandung

Abstract
This paper presents an optimization of 3-phase AC motor power consumption by means of intelligent control signal. The control signal is generated by the controller consists of Proportional, Integral and Derivative (PID) controller combined with fuzzy logic controller to produce the optimal control signal. The proposed controller is able to minimize the Root Mean Square Error (RMSE) of the response of motor. The PID controller parameters are obtained from the $H_{infty}$ synthesis of the full state feedback form of the motor, and fuzzy logic is designed to reject the noise and to flatten the motor-s response implemented using Raspberry Pi. By generating control signal with the controller, the electric power consumption of the 3-phase AC motor is reduced to 0.58 (4.32%), and the RSME of the motor-s response is decreased to 4.90 (12.26 %).

Keywords
3-phase AC Motor, electric power consumption, robust PID controller, fuzzy logic, Phyton, Raspberry Pi.

Topic
Control System

Link: https://ifory.id/abstract/VdX7ejhxQH4w

Corresponding Author
Mochammad Ariyanto

Institutions
a) Department of Mechanical Engineering
Diponegoro University
Semarang, Indonesia
*mochammad_ariyanto[at]ft.undip.ac.id
b) National Center for Sustainable Transportation Technology (NCSTT),
Indonesia

Abstract
This paper presents the development of a car model that can detect edge, line, and corner of the road and also the model can detect the red color of a traffic light. The car model is equipped with a camera that is used for computer vision purpose. The image comes from a camera is read by using Raspberry Pi single board computer. The algorithms for image processing method are selected to detect edge, line, corner and traffic light of the road model. The algorithms are developed in Simulink diagram block and embedded into Raspberry Pi using Simulink Support Package for Raspberry Pi Hardware. The embedded algorithms for detecting line, edge, corner and red color of traffic light will be tested. The test will be conducted in real time mode. Based on the test results, the embedded image processing algorithms can successfully detect line, edge, and corner of the road image, and it can detect the red color of traffic light image.

Keywords
image processing; Raspberry Pi; real time; car model

Topic
Control System

Link: https://ifory.id/abstract/4B2Ga3RZcJAH

Corresponding Author
Bernard Renardi

Institutions
Institut Teknologi Bandung (ITB)

Abstract
The development of road infrastructures, especially in developing countries such as Indonesia, continues significantly in the last decade. Along with the acceleration of development that has resulted in 406.14 kilometers of new roads in the last 5 years, an updated road map is needed as rapid as the growth of these roads proportionally. To solve this problem, commonly used technology takes three years to update the map and still unable to map the entire road, especially those that can only be passed by smaller vehicles. In this paper, an alternative mapping technique using multi-quadrotor system is introduced for updating the road map effectively. Multi-quadrotor system allows that the terrain mapping can be larger compared to single quadrotor system. The designed system is an integration of two Robot Operating System (ROS) packages as the framework for the software development, which is ardrone_autonomy and tum_ardrone. The multi-quadrotor will take images of contour using a 720p front camera with frequency of 2 – 4 Hz while flying. The images taken with a required specification will be processed into a new map of the area using Agisoft Photoscan. This new map will be processed by a YOLO-based object detection algorithm for specific object identification purpose. Real-time experimental results using two AR.Drone 2.0 showed that successful image recognition was obtained with high resolution images of map.

Keywords
multi-quadrotor, robot operating system, image recognition, AR. Drone 2.0, YOLO

Topic
Control System

Link: https://ifory.id/abstract/GNJqUkFcdRyB

Corresponding Author
Imam Boni Mores

Institutions
a)Instrumentation and Control Research Group,
Department of Engineering Physics, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132, Indonesia

b)National Center for Sustainable Transportation Technology, CRCS Building, 2nd floor, Jl. Ganesha 10, Bandung 40132, Indonesia

*yul[at]tf.itb.ac.id

Abstract
Particle Swarm Optimization (PSO) and Brain Storm Optimization (BSO) are alternative methods to find out the optimized solution of a non-linear equation. This paper will discuss the application of both methods to find out the weight of neurons from Adaptive Neuro Fuzzy Inference Systems (ANFIS) technique, which is used in predicting the bus arrival time at the bus stop. Comparison of the performance from both methods will also be made. After the modeling, training and testing of the proposed algorithm, the RMSE value produced from ANFIS which was trained by the PSO testing was 0.8145, and if it was trained by BSO was 0.8352. These results also conclude that the ANFIS with PSO algorithm yields better predicting bus arrival time better rather than ANFIS BSO in this case

Keywords
Adaptive Neuro-fuzzy Inference System, bus arrival time, Brain Storm Optimization, Particle Swarm Optimization

Topic
Control System

Link: https://ifory.id/abstract/dvpUFA3KcTwB