Project

Minimal information model multi-objective predictive control for multivariable systems (MIMOPREC)

Code

01N02018

Duration

01 January 2018 → 31 December 2021

Funding

Regional and community funding: Special Research Fund

Promotor

Clara Ionescu

Research disciplines

Engineering and technology
- Automation and control systems
- Renewable power and energy systems engineering
- Computer aided engineering, simulation and design
- Control engineering
- Motion planning and control
- Systems theory, modelling and identification

Keywords

predictive control interacting systems adaptive control automatic tuning robustness stability cross-disciplinary applications

Project description

This project aims to deliver a new methodology tailored for industrial operators to tune and manage process control by model predictive control strategies in a user-friendly, mixed heuristicmathematic context. The main innovative character is that it no longer requires availability of an accurate prediction model of the complex dynamic process to be controlled with multi-objective optimization.