- Dynamical systems analysis (stability, robustness, and perturbation theory)
- Control (feedback linearization, motion planning and trajectory tracking)
- Observation (estimation, asymptotic observer, filtering and diagnosis).
Programme: Examples from both industrial and academic worlds serve as introduction and illustration for several key definitions and results. These yield classes of control and observation algorithms. More theoretical results stemming from this approach are presented, and, most importantly, we stress their limitations by sketching perspectives toward open problems. Numerical experiments (conducted with Scilab) motivate the need for robustness and performance. They also underline the roles of (large-scale) simulation models and low dimensional control design oriented models. Mainly, we focus on systems governed by continuous-time ordinary differential equations. Discrete time systems fundamentals are given as an appendix.
Last Modification : Saturday 11 December 2010