Monitoring the Condition of Non-linear Packaging Materials Subject to Varying Excitation Levels Using a Reverse Multiple Input/Single Output Based Approach

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.

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

IET Communications ◽

10.1049/iet-com.2014.0310 ◽

2015 ◽

Vol 9 (3) ◽

pp. 396-403 ◽

Cited By ~ 35

Author(s):

Zheng Chu ◽

Kanapathippillai Cumanan ◽

Zhiguo Ding ◽

Mai Xu

Keyword(s):

Output Channel ◽

Secrecy Rate ◽

Single Output ◽

Multiple Input ◽

Device To Device

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

Energi & Kelistrikan ◽

10.33322/energi.v12i2.1000 ◽

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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Application of multiple-input/single-output analysis procedures to flight test data

Journal of Guidance Control and Dynamics ◽

10.2514/3.20686 ◽

1991 ◽

Vol 14 (3) ◽

pp. 645-651 ◽

Cited By ~ 1

Author(s):

J. K. Sridhar ◽

G. Wulff

Keyword(s):

Test Data ◽

Flight Test ◽

Output Analysis ◽

Single Output ◽

Multiple Input

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A MISO-ARX-Based Method for Single-Trial Evoked Potential Extraction

BioMed Research International ◽

10.1155/2017/7395385 ◽

2017 ◽

Vol 2017 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Nannan Yu ◽

Lingling Wu ◽

Dexuan Zou ◽

Ying Chen ◽

Hanbing Lu

Keyword(s):

Evoked Potential ◽

Moving Average ◽

Extraction Process ◽

Autoregressive Moving Average ◽

Single Trial ◽

Model Driven ◽

Single Output ◽

Multiple Input ◽

Novel Method ◽

Electroencephalographic Activity

In this paper, we propose a novel method for solving the single-trial evoked potential (EP) estimation problem. In this method, the single-trial EP is considered as a complex containing many components, which may originate from different functional brain sites; these components can be distinguished according to their respective latencies and amplitudes and are extracted simultaneously by multiple-input single-output autoregressive modeling with exogenous input (MISO-ARX). The extraction process is performed in three stages: first, we use a reference EP as a template and decompose it into a set of components, which serve as subtemplates for the remaining steps. Then, a dictionary is constructed with these subtemplates, and EPs are preliminarily extracted by sparse coding in order to roughly estimate the latency of each component. Finally, the single-trial measurement is parametrically modeled by MISO-ARX while characterizing spontaneous electroencephalographic activity as an autoregression model driven by white noise and with each component of the EP modeled by autoregressive-moving-average filtering of the subtemplates. Once optimized, all components of the EP can be extracted. Compared with ARX, our method has greater tracking capabilities of specific components of the EP complex as each component is modeled individually in MISO-ARX. We provide exhaustive experimental results to show the effectiveness and feasibility of our method.

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