Abstract Model-based predictive control (MPC) describes a set of advanced control
methods, which make use of a process model to predict the future behavior of the controlled …

Due to the fast advancement of communication and information technology, intelligent
buildings have garnered great interest. These buildings can forecast weather, ambient …

This paper presents the acados software package, a collection of solvers for fast embedded
optimization intended for fast embedded applications. Its interfaces to higher-level …

We propose a methodology for the identification of nonlinear state–space models from
input/output data using machine-learning techniques based on autoencoders and neural …

Energy efficiency remains a significant topic in the control of building heating, ventilation,
and air-conditioning (HVAC) systems, and diverse set of control strategies have been …

Motivated by the fact that many nonlinear plants can be represented through Linear
Parameter Varying (LPV) embedding, and being this framework very popular for control …

Developing methods for autonomous landing of an unmanned aerial vehicle (UAV) on a
mobile platform has been an active area of research over the past decade, as it offers an …

Abstracts Over the past few decades, advanced process control (APC) such as model
predictive control (MPC) has been introduced to process industry to enhance its operational …

For safety-critical applications, the validation process using a model-based approach plays
an increasingly important role. In this paper we propose the application of a predictive …

Modern agriculture represents an economic sector that can mainly benefit from technology
innovation according to the principles suggested by Industry 4.0 for smart farming systems …