A HILBERT TRANSORM APPROACH IN SOURCE IDENTIFICATION VIA MULTIPLE-INPUT SINGLE-OUTPUT MODELING FOR CORRELATED INPUTS

1998 ◽  
Vol 12 (4) ◽  
pp. 501-513 ◽  
Author(s):  
B.-K. Bae ◽  
K.-J. Kim
Keyword(s):  
Source Identification ◽  
Single Output ◽  
Multiple Input

Source Identification Using Multi-Input/Single-Output Modeling and Causality Checking of Correlated Inputs

1994 ◽  
Vol 116 (2) ◽  
pp. 232-236 ◽  
Author(s):  
Jung-Seok Park ◽  
Kwang-Joon Kim
Keyword(s):  
Source Identification ◽  
Coherence Function ◽  
Experimental Results ◽  
Partial Coherence ◽  
Impulse Response Functions ◽  
Single Output ◽  
Multiple Input ◽  
Time Region ◽  
Correlated Signals

This paper presents experimental results of a case study of source identification using multiple-input/single-output modeling in a case where the inputs are coherent to some extent and, hence, the priority among the correlated inputs must be decided before applying the partial coherence function approach. The basic idea is that either one of any two correlated signals causes the other and that this causality can be checked by observing the impulse response functions estimated in the negative time region, interpretations of which are provided for a system transfer function given in the fractional form of polynomials and for a case of wave propagation. The experimental results from a three inputs/single output acoustical system shows that the method works well and is promising in the source identification problems with coherent inputs.

Estimation Design Using Youla Parametrization With Automotive Applications

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Francis Assadian ◽  
Alex K. Beckerman ◽  
Jose Velazquez Alcantar
Keyword(s):  
Kalman Filtering ◽  
Feedback Stabilization ◽  
Estimation Technique ◽  
Single Input Single Output ◽  
Normal Forces ◽  
Single Output ◽  
Multiple Input ◽  
Single Input ◽  
Established Technique ◽  
Better Than

Youla parametrization is a well-established technique in deriving single-input single-output (SISO) and, to a lesser extent, multiple-input multiple-ouput (MIMO) controllers (Youla, D., Bongiorno, J. J., Jr., and Lu, C., 1974, “Singleloop Feedback-Stabilization of Linear Multivariable Dynamical Plants,” Automatica, 10(2), pp. 159–173). However, the utility of this methodology in estimation design, specifically in the framework of controller output observer (COO) (Ozkan, B., Margolis, D., and Pengov, M., 2008, “The Controller Output Observer: Estimation of Vehicle Tire Cornering and Normal Forces,” ASME J. Dyn. Syst., Meas., Control, 130(6), p. 061002), is not established. The fundamental question to be answered is as follows: is it possible to design a deterministic estimation technique using Youla paramertization with the same robust performance, or better, than well-established stochastic estimation techniques such as Kalman filtering? To prove this point, at this stage, a comparative analysis between Youla parametrization in estimation and Kalman filtering is performed through simulations only. In this paper, we provide an overview of Youla parametrization for both control and estimation design. We develop a deterministic SISO and MIMO Youla estimation technique in the framework of COO, and we investigate the utility of this method for two applications in the automotive domain.

Robust secrecy rate optimisations for multiuser multiple-input-single-output channel with device-to-device communications

2015 ◽  
Vol 9 (3) ◽  
pp. 396-403 ◽  
Author(s):  
Zheng Chu ◽  
Kanapathippillai Cumanan ◽  
Zhiguo Ding ◽  
Mai Xu
Keyword(s):  
Output Channel ◽  
Secrecy Rate ◽  
Single Output ◽  
Multiple Input ◽  
Device To Device

scholarly journals Evaluasi Performa Fuzzy Logic Controller untuk mengatur kecepatan Motor DC Penguatan Terpisah

2020 ◽  
Vol 12 (2) ◽  
pp. 100-110
Author(s):  
Muhammad Aditya Ardiansyah ◽  
Renny Rakhmawati ◽  
Hendik Eko Hadi Suharyanto ◽  
Era Purwanto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Duty Cycle ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Boost Converter ◽  
Voltage Source ◽  
Single Output ◽  
Multiple Input ◽  
State Error

Beragamnya metode yang ditawarkan oleh fuzzy logic kontroller membuat sebagaian orang meneliti mengenai perbedaan metode inferensi yang digunakan oleh fuzzy logic controller. Sejauh ini terdapat tiga metode fuzzy logic kontroller yang telah dikembangkan yaitu Mamdani, Sugono dan Sukamoto. Pada jurnal ini penggunaan fuzzy logic kontroller akan dievaluasi dengan menggunakan motor dc penguat terpisah sebagai beban untuk melakukan pengaturan kecepatan motor dc. Pada paper ini tujuan utamanya adalah dapat mengendalikan kecepatan dari motor DC Penguatan Terpisah dengan mengatur tegangan jangkar dari motor tersebut. DC motor merupakan salah satu jenis motor memiliki banyak aplikasi dan memiliki kemudahan untuk mengatur kecepatan pada motor tersebut. Logika fuzzy yang digunakan pada studi ini adalah inferensi sugeno dimana dengan konfigurasi Multiple Input Single Output (MiSo). Dimana input berupa error dan perubahan error dan output berupa duty cycle dikarenakan yang dikendalikan oleh logika fuzzy adalah Boost Converter selaku controlled voltage source. Target pada jurnal ini adalah dari kecilnya nilai steady – state error dan minimnya osilasi sehingga mampu membuat sistem lebih stabil. Pada studi ini, Hasil pengujian dilakukan dengan menggunakan Simulink by Matlab dengan Hasil pengujian berupa error rata rata sebesar 5.36%.

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