Online suboptimal control of linearized models

Identification of Linearized Models and Robust Control of Physical Systems

This chapter presents the design of a controller that ensures both the robust stability and robust performance of a physical plant using a linearized identified model . The structure of the plant and the statistics of the noise and disturbances affecting the plant are assumed to be unknown. As the design of the robust controller relies on the availability of a plant model, the mathematical mode...

Computational Efficiency of Suboptimal Nonlinear Predictive Control with Neural Models

This paper studies computational efficiency of suboptimal Model Predictive Control (MPC) with neural models. The algorithm requires solving on-line only a quadratic optimisation problem. Considering a nonlinear polymerisation process, for which the linear MPC algorithm is inadequate, it is shown that the suboptimal algorithm results in closedloop control performance similar to that obtained in ...

Low-order models : optimal sampling and linearized control strategies

We propose an optimal sampling strategy to build a robust low-order model. This idea is applied to the construction of a vortex wake model accurate for several regimes. In addition we explore the relationships between unstable modes and low-order modelling. An example of control based on a linearized approach is presented. Résumé : Nous proposons une méthode d'´ echantillonnage optimale pour co...

Suboptimal Control of Fluid Flows1

Low-Dimensional Models for Control of Leading-Edge Vortices: Equilibria and Linearized Models

When an airfoil is pitched up rapidly, a dynamic stall vortex forms at the leading edge and produces high transient lift before shedding and stall occur. The aim of this work is to develop low-dimensional models of the dynamics of these leading-edge vortices, which may be used to develop feedback laws to stabilize these vortices using closed-loop control, and maintain high lift. We first perfor...