Research

The main mission of the research group CS (Control Systems) is to develop new methodologies for the design of advanced multivariable controls that make systems react autonomously and optimally. Research revolves around PID control of chemical process dynamic systems, with specific emphasis on developing new algorithms for real-time control, optimization, process identification and machine learning. Besides focusing on algorithms and understanding their theoretical properties, research results are constantly applied to real-life problems of industrial systems.

• Process models are needed to better analyze and design controllers for processes. We are currently investigating methods for parameter estimation of nonlinear continuous-time systems as well as unstable systems. The development of tuning techniques is being explored for use in on-line for process control.

• Models are not perfect; therefore, a key aspect in my research is the implementation of uncertainty analyses to assess process variability under uncertainty. I strongly believe that model uncertainty is essential for designing efficient mathematical tools that can be realistically applied in practice for process improvement.

• We develop methods and procedures used by thousands of practitioners, researchers and students around the world for process control system analysis, tuning and training.
• We want to find an improved control structure where acceptable operation under all conditions is achieved with constant set-points for the controlled variables.
  • More generally, the idea is to use the model off-line to find properties of the optimal solution suited for on-line implementation.
  • Current research efforts in our lab seek to extend these methods to such important areas as:
    • PID Controller Tuning, Multivariable Controller Design
    • whole-plant modeling, simulation and control.
    • automated controller design and tuning.
    • controller performance monitoring.
    • multivariable process identification and control.
    • Unstable System Stabilization
    • Process Dynamics and Control and Nonlinear Systems and Analysis
• IoT, Image Processing, Big Data and Machine Learning in Process Industry.