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MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data. [PDF]

Microbiome
Dawkins JJ, Gerber GK.
europepmc   +1 more source

ybyra: Y-chromosome haplogroup calling using a tree-based scoring method

Pinotti T, McColl H, Sikora M, Czech L.
europepmc   +1 more source

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Revisiting the Mit Rule for Adaptive Control

IFAC Postprint Volumes IPPV / International Federation of Automatic Control, 1987
Abstract The MIT rule is a scalar parameter adjustment law which was proposed in 1961 for the model reference adaptive control of linear systems modeled as the cascade of a known stable plant and a single unknown gain. This adjustment law was derived by approximating a gradient descent procedure for an integral error squared performance criterion ...
Iven M Y Mareels, Brian D O Anderson, Robert R Bitmead   +2 more
exaly   +4 more sources

Control of a Coupled CSTR Process using MRAC-MIT Rule

2019 Innovations in Power and Advanced Computing Technologies (i-PACT), 2019
Chemical processes can be controlled using a continuous stirred tank reactor (CSTR) in process industries. A CSTR is a highly non-linear system and this non-linearity makes the chemical process unstable. This proposed work deals with the temperature control of cascadedCSTR by implementing model reference adaptive control (MRAC) method based on MIT rule.
Eva Mathew, Tanmay Pawar, B Jaganatha Pandian   +2 more
exaly   +2 more sources

Simulation of MIT Rule-Based Adaptive Controller of a Power Plant Superheater

Advances in Intelligent and Soft Computing, 2012
MIT rule is one of the basic techniques of adaptive control. It can be embedded into a general scheme of circuit with MRAC structure (reference adaptive controller). This paper deals with simulation of MRAC by use of MIT rule for a superheater which is a crucial part of a coal-fired power plant. A superheater has been chosen as a typical practical real
Zdenek Machacek, Martin Pies, Stepan Ozana   +2 more
exaly   +2 more sources

Modeling and Analysis of Model Reference Adaptive Control by Using MIT and Modified MIT Rule for Speed Control of DC Motor

2017 IEEE 7th International Advance Computing Conference (IACC), 2017
Normal feedback controllers may not perform well, because of the variations in process or Plant due to nonlinear actuators, changes in environmental conditions. The design of a controller for speed control of DC Motor with Model Reference Adaptive Control scheme using the MIT rule for adaptive mechanism is presented in this paper.
M. Swathi, P. Ramesh
exaly   +2 more sources

A Stability Analysis of Inverted Pendulum System Using Fractional-Order MIT Rule of MARC Controller

Advances in Intelligent Systems and Computing, 2018
In this paper, modification of MIT rule of MARC (Model Adaptive Reference Controller) using fractional derivative concept has been proposed for an integer-order-inverted pendulum system which is highly unstable. Here, the G-L fractional derivative method has been proposed to design fractional-order MIT rule of MARC controller.
Deep Mukherjee, Palash Kundu, Apurba Ghosh   +2 more
exaly   +2 more sources