Multivariable Process Control using Multiobjective Optimization Techniques and Computational Intelligence Algorithms (LP-MOP 1.0)

This project addresses the growing challenge of controlling complex multivariable processes, where traditional control techniques prove limited or inefficient due to high operational demands. The primary objective is to develop and implement advanced control strategies. The methodology will focus on applying multi-objective optimization and utilizing computational intelligence algorithms to enhance control performance. Approaches such as centralized and decentralized control will be explored and compared, acknowledging their respective advantages and disadvantages in the context of complex systems. The expected outcome is the formulation of robust and efficient control strategies that overcome the limitations of conventional methods in advanced industrial and scientific environments.<br/><br/><b>Goal</b>: <br/>To design control strategies for multivariable processes utilizing advanced multi-objective optimization techniques and computational intelligence algorithms to address the increasing complexity of these systems.<br/><br/><b>Research lines</b>: <br/>Control engineering and automation technologies