Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

Purdue faculty dedicate countless hours to exploring the frontiers of their respective fields, pushing the boundaries of knowledge and contributing to the ever-evolving landscape of academia. To ...

Description: Basics of numerical optimization: problem formulation, conditions of optimality, search direction and step length. Calculus-based techniques for univariate and multivariate optimization.

When model-based multivariable control made its debut in the 1980s, it was expected that process models, once acquired through a plant step test, would be durable and long lived. However, this ...

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