Cahyani, Nurdia Dwi (2021) Implementasi Ensemble Kalman Filter Dan Kontrol Konsensus Pada Sistem Gerak Multi-Robot. Masters thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 06111950010005-Master_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
06111950010005-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (3MB) | Request a copy |
|
Text
06111950010005-Master_Thesis.pdf Restricted to Repository staff only Download (3MB) | Request a copy |
Abstract
Selama beberapa dekade, perkembangan robot sangat signifikan seiring dengan perkembangan teknologi. Robot digunakan untuk membantu menyelesaikan tugas manusia. Pada awalnya, peneliti banyak melakukan penelitian terkait sistem gerak single-robot. Namun, pada kondisi tertentu single-robot tidak dapat membantu menyelesaikan tugas manusia dan tidak dapat bekerja dalam lingkungan berskala besar. Sehingga muncul penelitian baru yaitu sistem multirobot. Sistem multi-robot adalah sekelompok robot dalam lingkungan yang tidak diketahui yang diharapkan dapat bekerja secara kooperatif untuk tujuan tertentu. Pada penelitian ini, dilakukan implementasi metode Ensemble Kalman Filter untuk estimasi posisi pada sistem gerak multi-robot. Metode Ensemble Kalman Filter digunakan untuk mengestimasi berbagai persoalan berbentuk model sistem strongly nonlinear, dan telah ditunjukkan bahwa mampu menyelesaikan model sistem dinamik nonlinear dan ruang keadaan yang besar. Setelah dilakukan estimasi, juga dilakukan desain kontrol untuk mencapai tugas yang ditentukan sebelumnya. Desain kontrol dapat menggunakan kontrol konsensus yang didasari pada teori graf dan teori kontrol. Pada kontrol konsensus, graf-graf yang terhubung dimaksudkan menuju tujuan tertentu yaitu menuju titik kesepakatan. Setelah itu, juga dilakukan kontrol formasi sesuai tujuan yang diinginkan. Robot yang digunakan pada penelitian ini berjumlah n-unit robot, dimana n>1. Hasil dari implementasi Ensemble Kalman Filter pada sistem gerak multi-robot memperoleh estimasi yang baik dan kesalahan yang sangat kecil. Sedangkan implementasi kontrol konsesus dan kontrol formasi dapat bergerak sesuai kesepakan dan sesuai formasi yang telah ditentukan.
====================================================================================================
For decades, the robot is very significant with the advent of technology. Robots used are to help complete human tasks. Initially, researchers conducted a lot of research related to single-robot motion systems. However, under certain conditions, the single-robot cannot help complete human tasks and cannot work in large-scale environments. So it appears the new research that is the system multirobot. A Multi-robot system is a robot in an environment unknown to work cooperatively for a particular purpose. In this study, performed the implementation of the Ensemble Kalman Filter to estimate position on moving systems multi-robot. The Ensemble Kalman filter used to estimate various problems shaped model strongly nonlinear system and has shown that able to solve a dynamical system nonlinear model and the state of being big. After estimating, a control design will be carried out to achieve the predetermined task. Control design can use consensus control based on graph theory and control theory. In consensus control, the connected graphs are intended towards a specific goal, namely towards the point of agreement. The number of robots used in this research is n-robot units, where n>1. The results of the implementation of the Ensemble Kalman Filter on the multi-robot motion system to obtain goods estimates and very small errors. Meanwhile, the implementation of consensus control and formation control can move according to the agreement and according to the predetermined formation.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Multi-robot, Ensemble Kalman Filter, kontrol konsesus, kontrol formasi,Multi-robot, Ensemble Kalman Filter, consensus control, formation control. |
| Subjects: | Q Science > Q Science (General) > Q180.55.M38 Mathematical models Q Science > QA Mathematics > QA166 Graph theory Q Science > QA Mathematics > QA336 Artificial Intelligence Q Science > QA Mathematics > QA371 Differential equations--Numerical solutions Q Science > QA Mathematics > QA402 System analysis. Q Science > QA Mathematics > QA402.3 Kalman filtering. Q Science > QA Mathematics > QA614.8 Differentiable dynamical systems |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | Nurdia Dwi Cahyani |
| Date Deposited: | 31 Aug 2021 23:38 |
| Last Modified: | 31 Aug 2021 23:38 |
| URI: | http://repository.its.ac.id/id/eprint/90710 |
Actions (login required)
 |
View Item |