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All Journal Journal of the Indonesian Mathematical Society Civil Engineering Journal Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan Limits: Journal of Mathematics and Its Applications International Journal of Computing Science and Applied Mathematics Journal of Robotics and Control (JRC)
Tahiyatul Asfihani
Department Of Mathematics, Institut Teknologi Sepuluh Nopember
Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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 1 
THE MISSILE GUIDANCE ESTIMATION USING EXTENDED KALMAN FILTER-UNKNOWN INPUT-WITHOUT DIRECT FEEDTHROUGH (EKF-UI-WDF) METHOD Subchan, Subchan; Asfihani, Tahiyatul
Journal of the Indonesian Mathematical Society Volume 19 Number 1 (April 2013)
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.19.1.124.1-14

Abstract

This paper consider the estimation of the optimal missile guidance which the objective is to minimize the interception time and the energy expen-diture. The proposed Extended Kalman Filter-Unknown Input-Without Direct Feedthrough (EKF-UI-WDF) approach is to estimate the optimal missile guidance and the target acceleration as unknown input to the missile-target interception model. Unknown input is any type of signals without prior information from agiven state model or a measurement. The computational for the EKF-UI-WDF method and optimal missile guidance show the closest range to the missile-target is smaller than using the EKF. However the Mean Squared Error (MSE) of estimating the optimal missile guidance using EKF method is smaller than using EKF-UI-WDF method.DOI : http://dx.doi.org/10.22342/jims.19.1.124.1-14
THE MISSILE GUIDANCE ESTIMATION USING EXTENDED KALMAN FILTER-UNKNOWN INPUT-WITHOUT DIRECT FEEDTHROUGH (EKF-UI-WDF) METHOD Subchan Subchan; Tahiyatul Asfihani
Journal of the Indonesian Mathematical Society Volume 19 Number 1 (April 2013)
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.19.1.124.1-14

Abstract

This paper consider the estimation of the optimal missile guidance which the objective is to minimize the interception time and the energy expen-diture. The proposed Extended Kalman Filter-Unknown Input-Without Direct Feedthrough (EKF-UI-WDF) approach is to estimate the optimal missile guidance and the target acceleration as unknown input to the missile-target interception model. Unknown input is any type of signals without prior information from agiven state model or a measurement. The computational for the EKF-UI-WDF method and optimal missile guidance show the closest range to the missile-target is smaller than using the EKF. However the Mean Squared Error (MSE) of estimating the optimal missile guidance using EKF method is smaller than using EKF-UI-WDF method.DOI : http://dx.doi.org/10.22342/jims.19.1.124.1-14
ANALISIS MODEL LINTASAN NANOPARTIKEL MAGNET PADA PEMBULUH DARAH DI DALAM MEDAN MAGNET DENGAN METODE RUNGE KUTTA ORDE KE-EMPAT Ms. Tahiyatul Asfihani; Hesti Hastuti; Chairul Imron
Limits: Journal of Mathematics and Its Applications Vol 13, No 1 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1402.905 KB) | DOI: 10.12962/j1829605X.v13i1.1929

Abstract

Nanopartikel magnetik memiliki peran penting dalam dunia kedokteran modern yaitu sebagai obat yang ditargetkan oleh magnet. Obat yang ditargetkan oleh magnet tersebut disuntikan kedalam tubuh kemudian akan dibawa oleh darah mengalir ke seluruh tubuh. Untuk memperoleh hasil yang lebih optimal, diperlukan suatu model lintasan nanopartikel magnet didalam embuluh darah. Sistem tersebut dibantu dengan medan magnet yang diposisikan diluar tubuh. Dengan menggunakan metode Runge-kutta, diperoleh jarak antara pusat pembuluh darah dengan pusat medan magnet yang lebih tepat adalah 0.025 m dimana posisi lintasannya menuju kearah pusat medan magnet yaitu nol (z/Rm=0).
On The Lagrange Interpolation of Fibonacci Sequence Muhammad Syifa'ul Mufid; Tahiyatul Asfihani; Lukman Hanafi
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 2, No 3 (2016)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (254.179 KB) | DOI: 10.12962/j24775401.v2i3.2093

Abstract

Fibonacci sequence is one of the most common sequences in mathematics. It was first introduced by Leonardo Pisa in his book Liber Abaci (1202). From the first n + 1 terms of Fibonacci sequence, a polynomial of degree at most n can be constructed using Lagrange interpolation. In this paper, we show that this Fibonacci Lagrange Interpolation Polynomial (FLIP) can be obtained both recursively and implicitly.
Estimasi Tingkat Aktivasi Virus COVID-19 dengan Menggunakan Metode Kalman Filter (Studi Kasus: di Provinsi Jawa Timur) Asfihani, Tahiyatul; Agustina, Choiriyah Sapta; Hazmi, Ahmad Ulul
Jurnal Ilmiah Soulmath : Jurnal Edukasi Pendidikan Matematika Vol 10 No 1 (2022)
Publisher : Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (423.871 KB) | DOI: 10.25139/smj.v10i1.4410

Abstract

Abstract COVID-19 is a concern in several countries because the rate of spread is fast enough to cause many deaths. COVID-19 is a disease caused by SARS-Cov-2. In this study, the SARS-Cov-2 activation rate was estimated using the Kalman Filter. The SARS-Cov-2 activation rate is the rate of change of the exposed class (Exposed) who completed the incubation period into the infected class (Infected). The spread of the COVID-19 disease was approached by the SEIR mathematical model. The SARS-Cov-2 activation rate is a parameter of SEIR's mathematical model of COVID-19 spread. The simulation results show that the SARS-Cov-2 activation rate in East Java in October 2021 is 0.563. The RMSE value that indicates the level of accuracy of the estimation process is 0,08. Keywords: COVID-19, Parameter Estimation, Kalman Filter, East Java Abstrak COVID-19 menjadi perhatian di beberapa negara karena tingkat penyebarannya cukup cepat hingga mengakibatkan banyak kematian. COVID-19 merupakan penyakit yang disebabkan oleh virus SARS-Cov-2. Pada penelitian ini, tingkat aktivasi SARS-Cov-2 diestimasi menggunakan Kalman Filter. Tingkat aktivasi SARS-Cov-2 adalah tingkat perubahan individu terpapar (Exposed) yang selesai masa inkubasi dan masuk ke dalam kelas yang terinfeksi (Infected). Penyebaran penyakit COVID-19 didekati dengan model matematika SEIR. Tingkat aktivasi SARS-Cov-2 merupakan parameter dari model matematika penyebaran COVID-19 SEIR. Hasil simulasi menunjukkan bahwa tingkat aktivasi SARS-Cov-2 di Jawa Timur pada Oktober 2021 bernilai 0,563. Tingkat keakuratan proses estimasi ditunjukkan melalui nilai RMSE sebesar 0,08. Kata Kunci: COVID-19, Estimasi Parameter, Kalman Filter, Provinsi Jawa Timur.
Model Predictive Control Design under Stochastic Parametric Uncertainties Based on Polynomial Chaos Expansions for F-16 Aircraft Purnawan, Heri; Asfihani, Tahiyatul; Kim, Seungkeun; Subchan, Subchan
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21366

Abstract

Parametric uncertainty in a dynamical system has the potential to undermine the performance of a closed-loop controller designed through classical techniques. This paper presents a novel approach to stochastic model predictive control (SMPC) by employing the polynomial chaos expansion (PCE) method called PCE-based model predictive control (PCE-MPC). This method offers a more robust and efficient solution to tackle parameter uncertainties in dynamic systems. The PCE method is utilized to propagate uncertainties through orthogonal polynomials, and the Galerkin projection approach is employed to compute PCE coefficients via intrusive spectral projection (ISP). In Galerkin projection, the inner product involves an integration term, and the integration values are approximated using the Gauss-Legendre quadrature. This quadrature method precisely integrates the p-th order polynomial using 2p-1 points. The numerical case study focuses on the short-period mode of the F-16 aircraft model. Simulation results demonstrate the robust performance of the proposed method in the presence of parameter uncertainties, with system states converging to the original points for each parameter realization under various initial conditions. Comparison results indicate negligible differences between MPC and PCE-MPC, showcasing nearly identical performance. However, further investigation is warranted in other cases and more complex systems involving parameter uncertainties.
DESIGN CONTROL OF SURFACE MARINE VEHICLE USING DISTURBANCE COMPENSATING MODEL PREDICTIVE CONTROL (DC-MPC) Cahyaningtias, Sari; Asfihani, Tahiyatul; Subchan, Subchan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 1 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (758.212 KB) | DOI: 10.30598/barekengvol15iss1pp167-178

Abstract

This research studied ship motion control by considering four degrees of freedom (DoF): yaw, roll, sway, and surge in which comprehensive mathematical modeling forming a nonlinear differential equation. Furthermore, this research also investigated solutions for fundamental yet challenging steering problems of ship maneuvering using advanced control method: Disturbance Compensating Model Predictive Control (DC-MPC) method, which based on Model Predictive Control (MPC). The DC-MPC allows optimizing a compensated control then consider sea waves as the environmental disturbances. Those sea waves influence the control and also becomes one of the constraints for the system. The simulation compared the varying condition of Horizon Prediction (Np) and another method showing that the DC-MPC can manage well the given disturbances while maneuvering in certain Horizon Prediction. The results revealed that the ship is stable and follows the desired trajectory
Analysis of GNSS-IMU Lidar Integration for Indoor Positioning Using Unscented Kalman Filter Amelia Nuri Ila, Qarina Putri; Cahyadi, Mokhamad N.; Asfihani, Tahiyatul; Suhandri, Hendy F.; Taufany, Fadlilatul
Civil Engineering Journal Vol. 11 No. 8 (2025): August
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-08-06

Abstract

Accurate navigation systems are important in various vehicle applications, both indoors and outdoors. Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) are sensors that are often used in vehicle navigation systems. GNSS has the advantage of providing accurate position and speed information, IMU is able to make measurements without being affected by environmental conditions, and LiDAR sensors can model the environment; however, the limited signal on GNSS in indoor environments results in decreased position accuracy. The development of GNSS-IMU integration has been widely carried out, one of which is by adding a LiDAR sensor. In this study, an improvement will be made to the integration algorithm on Vision RTK2, which produces GNSS-IMU coordinate data, and Backpack Lidar, which can display 3D visualization on the traversed path using the Unscented Kalman Filter (UKF) method to improve navigation accuracy, especially in indoor environments. The results of the study showed that the UKF simulation and free outage conditions showed high accuracy with RMSE of 0.00308 m and 0.00175 m for the Easting and Northing positions and MAE of 0.00088 m and 0.00024 m. However, in outage conditions, the RMSE values were 4.0881 m and 8.6317 m, and MAE of 5.9871 m and 7.4182 m. The results of the 3D point cloud of the LiDAR model that had been georeferenced using the UKF fusion results and the KKH calculation results were validated using a rolling meter. Validation of point cloud processing from the 3D LiDAR model using a rolling meter and georeferencing with KKH calculations showed a small RMSE value, which was 0.3420 m, and 0.0354 m for the distance dimension with a rolling meter. 0.6358 m for georeferenced RMSE using UKF fusion data, and 0.0779 for distance dimension using roll meters. The small RMSE results indicate a high level of agreement between point cloud data and measurements using a rolling meter used as reference data. This study shows that the integration of GNSS-IMU sensors with LiDAR using the UKF method can improve the accuracy and reliability of indoor navigation systems.
Co-Authors Agustina, Choiriyah Sapta Amelia Nuri Ila, Qarina Putri Cahyadi, Mokhamad N. Cahyaningtias, Sari Chairul Imron, Chairul Fadlilatul Taufany Hazmi, Ahmad Ulul Hesti Hastuti Kim, Seungkeun Lukman Hanafi Muhammad Syifa'ul Mufid Purnawan, Heri Subchan Subchan Subchan, Subchan Suhandri, Hendy F.