Implementation of numerical optimization algorithms in MATLAB, including derivative-free and gradient-based methods for unconstrained problems, and projection techniques for constrained optimization.

Multivariable control systems design and optimization addresses the task of regulating multiple interdependent process variables within a single framework. Unlike single‐loop controllers, ...

Optimization – though not necessarily real-time optimization – is always part of multivariable control. Multivariable control is a multi-loop control strategy that does not aim for a single operating ...

I am delighted to announce the completion of my research project, which focuses on comparing algorithms for solving multivariable unconstrained nonlinear programming problems. Enclosed herein are the ...

In this article, as in industry, advanced process control (APC) refers primarily to multi-variable control. Multivariable control means adjusting multiple single-loop controllers in unison, to meet ...

Abstract: Robustness of Model Predictive Control (MPC) has been extensively investigated, considering both on-line and off-line strategies. However the implementation of the theoretical background ...

This project implements a Single Layer Neural Network (SLNN) from scratch using Matlab. It focuses on the theoretical application and practical comparison of unconstrained optimization algorithms ...

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 ...

College of Mathematics and Information Science, Guangxi University, Nanning, China. School of Mathematical Science, Guangxi Teachers Education University, Nanning, China.. It is well known that the ...