scholarly journals Simulation Study on State Estimation for a Quadrotor Generalized Attitude Model

2021 ◽  
Vol 1914 (1) ◽  
pp. 012043
Author(s):  
H Yin ◽  
J C Liu ◽  
L H Geng ◽  
S H Zhao ◽  
T B Ayele
2019 ◽  
pp. 29-38
Author(s):  
Samia Semcheddine ◽  
Hanane Bouchareb

The production of biogas via an anaerobic fermentation process is very interesting for various reasons: it not only produces renewable energy, but also facilitates the disposal of organic waste, therefore it preserves the environment, it contributes to the resolution of energy problems in agriculture and agro industry, it’s available for everyone because the waste is available everywhere. This process takes place in continuously stirred tank bioreactor and is described by a highly nonlinear model whose parameters are often uncertain thereby requiring robust control in any process performance enhancement procedure to optimize the biogas production. Thus a robust control technique, synergetic, is proposed to improve the settling time in a fermentation based biogas production in a simulation study; the simulation study is carried out on biotechnological process described by a five-order continuous-time reaction scheme described by three stages. An extended Luenberger observer is proposed under synergetic control to observe the different concentrations because of the high-cost and unavailable measurement instrumentation. The interest of paper lies in controlling the amount of bio methane produced and the observation of all the states of the system (5 different populations of the complex community of bacteria and substrate concentrations acting during anaerobic digestion (AD) processes) by simply measuring the biogas produced. The monitoring, controller and observer performance are evaluated via numerical simulations showing excellent responses under the influence of control input. Key words: Bio methane, anaerobic digestion, synergetic control, extended Luenberger observer, state estimation.


2006 ◽  
Vol 11 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Alexander von Eye

At the level of manifest categorical variables, a large number of coefficients and models for the examination of rater agreement has been proposed and used. The most popular of these is Cohen's κ. In this article, a new coefficient, κ s , is proposed as an alternative measure of rater agreement. Both κ and κ s allow researchers to determine whether agreement in groups of two or more raters is significantly beyond chance. Stouffer's z is used to test the null hypothesis that κ s = 0. The coefficient κ s allows one, in addition to evaluating rater agreement in a fashion parallel to κ, to (1) examine subsets of cells in agreement tables, (2) examine cells that indicate disagreement, (3) consider alternative chance models, (4) take covariates into account, and (5) compare independent samples. Results from a simulation study are reported, which suggest that (a) the four measures of rater agreement, Cohen's κ, Brennan and Prediger's κ n , raw agreement, and κ s are sensitive to the same data characteristics when evaluating rater agreement and (b) both the z-statistic for Cohen's κ and Stouffer's z for κ s are unimodally and symmetrically distributed, but slightly heavy-tailed. Examples use data from verbal processing and applicant selection.


Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.


Methodology ◽  
2015 ◽  
Vol 11 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jochen Ranger ◽  
Jörg-Tobias Kuhn

In this manuscript, a new approach to the analysis of person fit is presented that is based on the information matrix test of White (1982) . This test can be interpreted as a test of trait stability during the measurement situation. The test follows approximately a χ2-distribution. In small samples, the approximation can be improved by a higher-order expansion. The performance of the test is explored in a simulation study. This simulation study suggests that the test adheres to the nominal Type-I error rate well, although it tends to be conservative in very short scales. The power of the test is compared to the power of four alternative tests of person fit. This comparison corroborates that the power of the information matrix test is similar to the power of the alternative tests. Advantages and areas of application of the information matrix test are discussed.


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