Results 31 to 40 of about 532,065 (295)

Decentralized active disturbance rejection control design for the gas turbine

open access: yesMeasurement + Control, 2020
As a clean energy engine, the gas turbine is widely used for the generation of the power plant and the propulsion of the warship. Its control is becoming more and more challenging for the reason that internal coupling exists and the load command changes ...
Gengjin Shi   +5 more
doaj   +1 more source

Tuning Rules for Active Disturbance Rejection Controllers via Multiobjective Optimization—A Guide for Parameters Computation Based on Robustness

open access: yesMathematics, 2021
A set of tuning rules for Linear Active Disturbance Rejection Controller (LADRC) with three different levels of compromise between disturbance rejection and robustness is presented. The tuning rules are the result of a Multiobjective Optimization Design (
Blanca Viviana Martínez   +3 more
doaj   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

open access: yesInternational Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam   +2 more
wiley   +1 more source

Reliable disturbance rejection [PDF]

open access: yesSba: Controle & Automação Sociedade Brasileira de Automatica, 2005
The paper studies the reliability (sensor and actuator failures) of the asymptotic disturbance rejection problem for linear time invariant systems using the factorization approach, assuming that not all loops fail simultaneously and that sensor and actuator do not fail simultaneously. The plant is two-output, i.e. two-vector-output, and the disturbance
openaire   +3 more sources

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch   +3 more
wiley   +1 more source

Disturbances rejection analysis and design of repetitive control system based on RC-EID

open access: yesFranklin Open
The article presents an analysis and design of disturbance rejection capabilities in repetitive control systems. This study aims to enhance disturbance rejection performance in repetitive control systems by integrating the equivalent-input-disturbance ...
Qingwen Lv   +3 more
doaj   +1 more source

Limits of Disturbance Rejection for Indirect Control [PDF]

open access: yesProceedings of the 44th IEEE Conference on Decision and Control, 2006
In many practical problems, the primary controlled variable is not available for feedback and is needed to be controlled indirectly using secondary measurements. We derive bounds on the H 2 and H ∞ optimal achievable performance for systems under indirect control, which have all scalar signals.
Arantza Sanz, Victor Etxebarria
openaire   +1 more source

Introduction to Interpersonal Acceptance-Rejection Theory (IPARTheory) and Evidence [PDF]

open access: yes, 2021
Interpersonal acceptance-rejection theory (IPARTheory) is an evidence-based theory of socialization and lifespan development. It is composed of three subtheories, each of which deals with a separate but interrelated set of issues.
Rohner, Ronald P., Ronald P. Rohner
core   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin   +14 more
wiley   +1 more source

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