Systems control (SC)
Team Head: Pr. BOUKAACHE Abdelnour
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Team Members:
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1. Objectives
The goal of this research team will be based on the development of advanced techniques for synthesizing robust multi-variable controllers. These controllers will be used to control different multidimensional processes namely uncertain, mal-conditioned, linear and non-linear systems. Practically, obtaining a robust multi-variable controller requires, a priori, a reliable and accurate model as possible to ensure a good description of the actual dynamics of the process to control. The optimal parameters of this model are then conditioned by the choice of an efficient identification technique in order to make a better estimate, and finally, the synthesis of the robust controller requires an efficient control technique allowing, on the one hand, the obtaining a good dynamic of tracking the reference signals and, on the other hand, obtaining a good dynamic of rejection of the disturbances which affect the model is for these reasons the collective work of the teams of this laboratory is essential.
Other objectives to achieve in this research team can summarize them by the following points:
- Perform efficient controls ensuring the looped system low decoupling output signals to those of references.
- Ensure a good margin of robustness of stability and the performances of the looped system for parametric variations structured or non-structured nevertheless considerable.
- Get reasonable orders from the practical point of view (non-expensive orders).
- Achieve better performance via basic and standard controllers by introducing parametrization techniques like Youla.
- Extend the application of advanced control techniques such as generalized predictive control, fuzzy control, neural control and neuro-fuzzy control on uncertain multi-variable systems.
2. Scientific foundations
- Synthesis of robust controllers by non-smooth optimization.
- Robustification of standard controllers.
- Multi-variable multi-delay systems control.
- Control of electrical machines by vector, scalar and other control
- Improved robustness of stability and performance through heuristic and meta-heuristic optimization.
- Polynomial formulation of the generalized predictive control law and robustness study in the presence of parametric or non-parametric model uncertainties.
- synthesis of robust controllers for non-linear multi-variable processes.
Keywords: Robust Control, Non-Smooth Optimization, Linear Inequality Matrices, Multi-Variable Systems.
