Estimasi Variabel Keadaan Gerak Longitudinal Pesawat Terbang Menggunakan Metode Fuzzy Kalman Filter

Resi Arumin Sani
Submission Date: 2016-07-22 15:44:37
Accepted Date: 2016-11-23 18:14:55

Abstract


Pesawat terbang merupakan sarana transportasi udara yang memiliki enam derajat kebebasan gerak (DOF) yaitu sistem gerak yang dikontrol oleh aileron, elevator dan rudder. Gerak longitudinal pesawat terbang dikontrol oleh sistem elevator. Sistem pengendalian gerak pesawat terbang dengan mempertimbangkan adanya suatu noise, sehingga dibutuhkan estimator yang digunakan untuk mengestimasi gerak pesawat terbang. Estimasi dilakukan dengan metode Kalman Filter dan kombinasi Logika Fuzzy-Kalman Filter yang disebut Fuzzy Kalman Filter, serta optimal smoothing. Berdasarkan hasil penelitian, nilai root mean square error (RMSE) menunjukkan bahwa metode Fuzzy Kalman Filter relatif lebih kecil daripada metode Kalman Filter pada semua variabel gerak longitudinal pesawat terbang. Peningkatan error variabel masing-masing yaitu kecepatan translasi ke depan 62,4 %, kecepatan translasi ke atas 0,7 %, kecepatan sudut pitch 0,009 % dan sudut pitch 1,7 %. Namun berdasarkan waktu komputasi, metode Kalman Filter lebih cepat dengan waktu  dibandingkan Fuzzy Kalman Filter yang membutuhkan waktu .

Keywords


Gerak Pesawat Terbang; Kalman Filter; Fuzzy Kalman Filter

References


D. McLean, Automatic Flight Control Systems. UK: Prentice Hall International (1990).

H. J. Zimmermann, Fuzzy Set Theory and Its Aplications. Second Revised Edition. United States: Kluwer Academic Publishers (1992), 2nd ed.

F. L. Lewis, Optimal Estimation with An Introduction to Stochastic Control Theory. School of Electrical Engineering Georgia Institute of Technology Atlanta. Georgia: (1998).

H. Mahmuri, “Estimasi Perkembangan Sel Kanker Menggunakan Fuzzy Kalman Filter,” Tesis Jurusan Matematika Institut Teknologi Sepuluh Nopember, Surabaya (2011).

G. Chen, Q. Xie, and L. S. Shieh, “Fuzzy Kalman Filter,” Journal Information of Information Sciences. No. 109 (1997) hal. 197-209.

A. Sukandi, “Pengendalian Gerak Longitudinal Pesawat Terbang dengan Metode Decoupling,” Jurusan Teknik Mesin Politeknik Negeri Jakarta (2010).

N. L. Gozali, A. S. Aisjah and E. Apriliani, “Estimasi Variabel Dinamik Kapal Menggunakan Metode Kalman Filter,” Jurnal Teknik POMITS Vol. 2, No. 1, Institut Teknologi Sepuluh Nopember Surabaya, (2013).

E. Apriliani, Subchan, F. Yunaini, and S. Hartini, “Estimation and Control Design of Mobile Robot Position,” Far East Journal of Mathematical Sciences (FJMS), PUSPHA PUBLISHER, Surabaya (2013).

A. Riski, M. I. Irawan, E. Apriliani, “Identifikasi Instrumen Gamelan Jawa Menggunakan Jaringan Fungsi Basis Radial dengan Metode Pelatihan Extended Kalman Filter,” Prosiding Seminar Nasional Matematika, Universitas Jember, (2014).


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