We consider the problem of optimal trajectory tracking for unknown systems. A novel data-
enabled predictive control (DeePC) algorithm is presented that computes optimal and safe …

Today, the stability of the electric power grid is maintained through real time balancing of
generation and demand. Grid scale energy storage systems are increasingly being …

The robust model predictive control (MPC) scheme of a perturbed nonlinear system is a
challenging problem because it is hard to not only obtain the estimated model and …

This work regards the design of optimization techniques for the purposes of state estimation
and control in the framework of inland waterways, often characterized by negligible bottom …

A multi-agent integrated distributed moving horizon estimation (DMHE) and model predictive
control (DMPC) framework is developed for complex process networks. This framework …

This article is concerned with the development and use of duality theory for a nonlinear
filtering model with white noise observations. The main contribution of this article is to …

This article is concerned with the development and use of duality theory for a hidden Markov
model (HMM) with white noise observations. The main contribution of this work is to …

A new estimation and control approach for the feedback control of an artificial pancreas to
treat Type 1 diabetes mellitus is proposed. In particular, we present a new output‐feedback …

When batteries supply behind-the-meter services such as arbitrage or peak load
management, an optimal controller can be designed to minimize the total electric bill. The …

A combined distributed moving horizon estimation and distributed model predictive control
architecture is proposed to address the distributed output–feedback control problem for …