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Journal : International Journal of Electrical and Computer Engineering

Attitude Control of Quadrotor Using PD Plus Feedforward controller on SO(3) Almido H Ginting; Oyas Wahyunggoro; Adha Imam Cahyadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (901.839 KB) | DOI: 10.11591/ijece.v8i1.pp566-575

Abstract

This paper proposes a simple scheme of Proportional-Derivative (PD) plus Feedforward controller on SO(3) to control the attitude of a quadrotor. This controller only needs the measurement of angular velocity to calculate the exponential coordinates of the rotation matrix. With rotation matrix as an error variable of the controller, the simulation shows that the controller is able to drive the attitude of the quadrotor from hovering condition to desired attitude and from an attitude condition goes to the hovering condition, despite the system is disturbed. When the system is convergent, the rotation error matrix will be a 3x3 identity matrix.
Inertial Navigation for Quadrotor Using Kalman Filter with Drift Compensation Lasmadi Lasmadi; Adha Imam Cahyadi; Samiadji Herdjunanto; Risanuri Hidayat
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (989.161 KB) | DOI: 10.11591/ijece.v7i5.pp2596-2604

Abstract

The main disadvantage of an Inertial Navigation System is a low accuracy due to noise, bias, and drift error in the inertial sensor. This research aims to develop the accelerometer and gyroscope sensor for quadrotor navigation system, bias compensation, and Zero Velocity Compensation (ZVC). Kalman Filter is designed to reduce the noise on the sensor while bias compensation and ZVC are designed to eliminate the bias and drift error in the sensor data. Test results showed the Kalman Filter design is acceptable to reduce the noise in the sensor data. Moreover, the bias compensation and ZVC can reduce the drift error due to integration process as well as improve the position estimation accuracy of the quadrotor. At the time of testing, the system provided the accuracy above 90 % when it tested indoor.
Path Planning Based on Fuzzy Decision Trees and Potential Field Iswanto Iswanto; Oyas Wahyunggoro; Adha Imam Cahyadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 1: February 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (367.221 KB) | DOI: 10.11591/ijece.v6i1.pp212-222

Abstract

The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path.
Hover Position of Quadrotor Based on PD-like Fuzzy Linear Programming Iswanto Iswanto; Oyas Wahyunggoro; Adha Imam Cahyadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 5: October 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (235.792 KB) | DOI: 10.11591/ijece.v6i5.pp2251-2261

Abstract

The purpose of this paper is to present the altitude control algorithm for quadrotor to be able to fly at a particular altitude. Several previous researchers have conducted studies on quadrotor altitude by using PID control but there are problems in the overshoot and oscillation. To optimize the control, tunning on PID algorithm must be first conducted to determine proportional and derivative constants. Hence, the paper presents altitude control modification by using PID-like fuzzy without tuning. The PID algorithm is a control algorithm for linear systems. While, system to be controlled is a non-linear, so that linearization is needed by using equilibrium. The proposed algorithm is a modification of the PID algorithm used as an altitude control which enables quadrotor to be stable when hovering. The algorithm used is not PID algorithm with tuning using fuzzy, but this is a single input single output (SISO) control PID-like fuzzy linear programming. The result of the research shows that quadrotor can hover in a rapid raise time, steady state and settling time without performing overshoot and oscillation.
Speed Control of a Single Taipei Mass Rapid Transit System Train by Using a Single Input Fuzzy Logic Controller Hari Maghfiroh; Oyas Wahyunggoro; Adha Imam Cahyadi; Kuo Lung Lian; Bwo Ren Ke
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 2: April 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (416.172 KB) | DOI: 10.11591/ijece.v6i2.pp621-629

Abstract

The purpose of this study was to design a speed controller for mass rapid transit (MRT) train by using a single input fuzzy logic controller (SIFLC). A complete train model, which was designed according to the design of a Taipei MRT train was used for analyzing both mechanical and electrical parts. The SIFLC was used for improving a fuzzy logic controller (FLC) by reducing its number of control rules. The results indicated that the SIFLC exhibited more favorable performance than the FLC did and a substantial reduction in the number of fuzzy rules and processing time. Therefore, tuning the SIFLC was easier compared with tuning the FLC; furthermore, the simulation time of the SIFLC was shorter than that of the FLC, exhibiting reductions of up to 17.3% in a constant track (track without gradient and curvature) and up to 12.27% in a variable track (track with gradient and curvature).