No abstract

This paper presents a gradient-based framework for plant and controller design of chaotic dynamical systems. The proposed approach uses a least-squares-shadowing method to perform the sensitivity analysis of the chaotic system and a first-order optimization algorithm to carry out the optimization process. Two different optimization strategies are examined. The first is a sequential approach, where the plant and control optimization problems are solved in series. The second is a simultaneous approach, where a single optimization problem is solved that considers both the plant and control disciplines at once. The two optimization strategies are applied to a simplified flow-control problem consisting of N potential vortices trapped inside a rectangular domain and controlled by one or more control vortices.

No abstract

No abstract