http://courses.ece.ubc.ca/574/Hjalmarsson_Automatica_March05.pdf

From experiment design to closed-loop control

Identification and control—closed-loop issues

This paper aims at introducing the reader to the various issues that arise in the development of a coherent methodology for the development of robust control design on the basis of models identified from data. When a reduced complexity model is identified with the purpose of designing a robust controller, the model is just a vehicle for the computation of a controller. The design of the identification and of the controller must be seen as two parts of a joint design problem. The central message of this paper is to show that the global control performance criterion must determine the identification criterion. This leads to non standard identification criteria, which can be minimized by appropriate experimental set-ups.

Towards a Joint Design of Identification and Control

Worst-case control-relevant identification

After several years of effort, constrained model predictive control (MPC), the de facto standard algorithm for advanced control in process industries, has finally succumbed to rigorous analysis. Yet successful practical implementations of MPC were already in place almost two decades before a rigorous stability proof for constrained MPC was published. What then, is the importance of recent theoretical results for practical MPC applications? In this publication we present a pedagogical overview of some of the most important recent developments in MPC theory and discuss their implications for the future of MPC theory and practice.

Model predictive controllers: A critical synthesis of theory and industrial needs

A criterion for system identification is developed that is consistent with the intended use of the fitted model for modern robust control synthesis. Specifically, a joint optimization problem is posed which simultaneously solves the plant model estimate and control design, so as to optimize robust performance over the set of plants consistent with a specified experimental data set. >

E. Mettler

Papers

A criterion for joint optimization of identification and robust control