Jurnal SINTA 2
Uji Performansi Ensemble Kalman Filter Untuk Mengurangi Noise Pengukuran Sensor Pada Robot
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 2 No. 2 (2015) · pp. 96–101
- ISSN
- 2528-6579, 2355-7699
- Published
- 2015-07-22
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakDalam penelitian ini diimplementasikan sebuah teknik robot bergerak yang berkaitan dengan kesetimbangan pada media tidak stabil. Tujuannya adalah merancang dan mengimplemntasikan sebuah sistem control diskrit digital yang memberikan stabilitas yang diperlukan. Kontrol PID dan Algoritma filter Kalman menjadi implementasi pengujian ideal model robot ini. Kedua algoritma tersebut mampu meningkatkan performa control pada sistem. Penelitian ini menguji kinerja sistem control PID dan Algoritma filter Kalman. Uji software dilakukan untuk mengumpulkan hasil kinerja kedua Algoritma kontroler PID dan Filter Kalman. Kinerja sistem kontrol secara langsung tergantung pada Algoritma filter Kalman dan parameter masukan controller PID. Penelitian ini menggunakan EnKF dan PID controller sebagai algoritma penyeimbang robot. Dilakukan tunning manual pada kovarian filter. Percobaan dilakukan dengan metode trial and error dengan mengubah-ubah matrik kovarian noise proses. Overshoot sistem bisa dikurangi dengan cara mengatur matrik kovarian noise proses. Dari hasil percobaan sistem optimal pada Q_accelerometer: 0.001, Q_gyroscope: 0.05, R_pengukuran: 0.03, P = 1790.005, I = 0.129 dan D = 96.881.Kata kunci: Ensemble Kalman, Kontroler PID, Performansi, RobotAbstractOne technique that is commonly used for mobile robots is an inverted pendulum based model. This research has been implementing a mobile robot technique in an unstable environment. The goal is to design and implementing a discrete digital control system that will provide robot stability. The PID controller algorithm and Ensemble Kalman filter (EnKF) implementation would be an ideal test model of this robot. Both of these algorithms are able to improve the performance of control systems. This robot already tested the performance of the PID control system and the EnKF algorithm. The performance of the PID controller algorithm and EnKF is tested by software. The Control system performance is directly dependent on the EnKF algorithm and input parameters of PID controller. Research uses EnKF algorithm and PID controller as a balancing robot. The covariance filter tuned by manually. Experiments carried out by the method of trial and error by varying the process noise covariance matrix. The system overshoot can be reduced by processing noise covariance matrix. The experiment results showed system optimal on Q_accelerometer: 0001, Q_gyroscope: 0.05 R_measurement: 12:03, P = 1790,005, I = 0.129 and D = 96 881.Keywords: Ensemble Kalman, Kontroler PID, Performance, Robots
Collaboration network of the authors
29 authors · 61 co-authorship links
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- University of Brawijaya
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Mochammad Hannats Hanafi Ichsan | University of Brawijaya | 5 |
| Dahnial Syauqy | University of Brawijaya | 4 |
| Edita Rosana Widasari | University of Brawijaya | 3 |
| Eko Setiawan | University of Brawijaya | 3 |
| Sabriansyah Rizqika Akbar | University of Brawijaya | 2 |
| Bayu Priyambadha | University of Brawijaya | 1 |
| Barlian Henryranu P. | Affiliation unknown | 1 |
| Heru Nurwarsito | University of Brawijaya | 1 |
| Denny Sagita Rusdianto | University of Brawijaya | 1 |
| Gembong Edhi Setyawan | University of Brawijaya | 1 |
| Kasyful Amron | University of Brawijaya | 1 |
| Rizky Kurnia A.M. | Affiliation unknown | 1 |
| Lindhu Parang Kusuma | University of Brawijaya | 1 |
| Eko Setiawan | University of Brawijaya | 1 |
| Ryzaldi Ananda Fabiana | University of Brawijaya | 1 |
| Syahrul Chilmi | University of Brawijaya | 1 |
| Septiyo Budi Perkasa | University of Brawijaya | 1 |
| Muhammad Fawwaz Dynoeputra Isnandar | University of Brawijaya | 1 |
| Rizal Maulana | University of Brawijaya | 1 |
| Fakhrul Allaam | University of Brawijaya | 1 |
| Rekyan Regasari Mardi Putri | University of Brawijaya | 1 |
| Irfan Muzakky Nurrizqy | University of Brawijaya | 1 |
| Rakhmadhany Primananda | University of Brawijaya | 1 |
| Arsal Wildan Naviaddin | University of Brawijaya | 1 |
| Jevandika | University of Brawijaya | 1 |
| Brylliano Maza Putra | University of Brawijaya | 1 |
| Syifa’ Hukma Shabiyya | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.