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Performance analysis of control allocation using data‐driven integral quadratic constraints

Advanced Control for Applications, Volume 4, Issue 4, December 2022., 2022
Abstract A new method is presented for evaluating the performance of a nonlinear control allocation system within a linear control loop. To that end, a worst‐case gain analysis problem is formulated that can be readily solved by means of well‐established methods from robustness analysis using integral quadratic constraints (IQCs).
Manuel Pusch, Daniel Ossmann, Harald Pfifer +2 more
wiley +1 more source

A Variational Beam Model for Failure of Cellular and Truss‐Based Architected Materials

Advanced Engineering Materials, EarlyView., 2023
Herein, a versatile and efficient beam modeling framework is developed to predict the nonlinear response and failure of cellular, truss‐based, and woven architected materials. It enables the exploration of their design space and the optimization of their mechanical behavior in the nonlinear regime. A variational formulation of a beam model is presented
Konstantinos Karapiperis +3 more
wiley +1 more source

Training Neural Networks with a Procedure Guided by BNF Grammars

Big Data and Cognitive Computing
Artificial neural networks are parametric machine learning models that have been applied successfully to an extended series of classification and regression problems found in the recent literature.
Ioannis G. Tsoulos , Vasileios Charilogis +1 more
doaj +1 more source

Optimization of surface roughness in CNC end milling using response surface methodology and genetic algorithm