Reinforcement learning (RL) has become a highly successful framework for learning in
Markov decision processes (MDP). Due to the adoption of RL in realistic and complex …

This article surveys the System Level Synthesis framework, which presents a novel
perspective on constrained robust and optimal controller synthesis for linear systems. We …

This paper addresses the optimal control problem known as the linear quadratic regulator in
the case when the dynamics are unknown. We propose a multistage procedure, called …

This paper develops a new framework to analyze and design iterative optimization
algorithms built on the notion of integral quadratic constraints (IQCs) from robust control …

The basic topic of this book is solving problems from system and control theory using convex
optimization. We show that a wide variety of problems arising in system and control theory …

For both their theoretical and practical impact, time-delay systems have been an enduring
theme in the study of differential equations, stochastic processes, game theory, and systems …

Robustness of control systems to disturbances and uncertainties has always been the
central issue in feedback control. Feedback would not be needed for most control systems if …

The LMI control toolbox Page 1 PKu"gsofths33rd Conferem on Deddon and control Lake
&remvi. FL- December 1894 TP-1 5:20 Tlie LMI Coiitrol Toolbox Puscal Guhiriet t Arkudii …

Before using interval analysis as a basic tool in the following chapters, we shall now
introduce its main concepts. Section 2.2 recalls fundamental notions on set operators, set …

This paper presents the development of a new course in the control curriculum dealing with
the control of systems subject to parametric uncertainty. This branch of Robust Control has …