In the past decade, moving horizon estimation (MHE) has emerged as a powerful technique for estimating the state of a dynamical system in the presence of nonlinearities and disturb...
Angelo Alessandri, Marco Baglietto, Giorgio Battis...
This paper deals with hierarchical model predictive control (MPC) of distributed systems. A threelevel hierarchical approach is proposed, consisting of a high level MPC controller,...
Jan Dimon Bendtsen, Klaus Trangbaek, Jakob Stoustr...
The paper presents an algorithm which combining a neural network observer, it give more flexible and accurate control on the engine operation. In recent year, several researchers ...
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...