Performansi Navigasi Robot Leader-Follower menggunakan Algoritma Logika Fuzzy Interval Tipe 2

Fitriana, Gita Fadila; Adhitama, Rifki

doi:10.29207/resti.v3i3.1094

Cited by 1 publication

(1 citation statement)

References 8 publications

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“…Pada tahapan fuzzifikasi mengubah masukan himpunan crisp ke himpunan fuzzy, bertujuan untuk tingkatan linguistiknya yang dikelompokkan dalam suatu variable fuzzy [15]. Logika Fuzzy Tipe 2 digunakan untuk menentukan keputusan pergerekan robot dalam mengatur jarak antara robot leader dan robot follower [16]. Tahapan yang hampir sama dengan Logika Fuzzy Tipe 1, perbedaan adalah setelah mendapatkan hasil dari keluaran inferensi, dilanjutkan dengan mereduksi untuk mengubah himpungan Logika Fuzzy Tipe 1 menjadi Logika Fuzzy Tipe 1, sehingga Logika Fuzzy Tipe 1 dilakukan defuzifikasi menjadi nilai tegas pada keluaran.…”

Section: Logika Fuzzy Tipe 2 -Particle Swarm Optimizationunclassified

Optimasi Performansi Pengendalian Robot Swarm menggunakan Logika Fuzzy Tipe 2-Particle Swarm Optimazation

Fitriana¹

2021

RESTI

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Robot control is currently very helpful for human work to be more effective and efficient both in completion time and in mitigating the risk of work accidents that may occur. This study determines the direction of the robot so that it does not collide with each other and reach the target. Controlling the swarm robot with the leader-follower approach uses Fuzzy Logic Type 2-Particle Swarm Optimization (PSO) to optimise the performance of the swarm robot. The Fuzzy Logic Method Type 2 measures the direction decisions of the leader robot and follower robot using a rule base of 8 rules; the leader-follower robot is given a target. Achieving targets using PSO, the PSO process looks for potential solutions with quality references to reach the target as the optimal solution. The leader-follower modelling has been modelled using kinematic equations and controlling the movement of the robot's trajectory in the form of a simulation that has been carried out. The measurement results based on robot data in an open environment are 110 data, and a square environment is 1342. The measurement results based on robot time in a four-obstacle environment have the fastest time of 10.83 seconds and the longest time environment in an oval environment of 134.9 seconds. The measurement results are based on resources in a free environment of 10.6 kb and a square environment of 49.1 kb. Fuzzy Logic Type 2-PSO has a higher time indicating a stable speed result and judging from the trajectory in avoiding obstacles, and the leader-follower robot has a faster response.

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Section: Logika Fuzzy Tipe 2 -Particle Swarm Optimizationunclassified

Optimasi Performansi Pengendalian Robot Swarm menggunakan Logika Fuzzy Tipe 2-Particle Swarm Optimazation

Fitriana¹

2021

RESTI

Self Cite

View full text Add to dashboard Cite

show abstract

Performansi Navigasi Robot Leader-Follower menggunakan Algoritma Logika Fuzzy Interval Tipe 2

Cited by 1 publication

References 8 publications

Optimasi Performansi Pengendalian Robot Swarm menggunakan Logika Fuzzy Tipe 2-Particle Swarm Optimazation

Optimasi Performansi Pengendalian Robot Swarm menggunakan Logika Fuzzy Tipe 2-Particle Swarm Optimazation

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