The industrial process monitoring and operating performance assessment techniques are of
great significance to ensure the safety and efficiency of the production and to improve the …

This paper introduces a variational formulation of natural selection, paying special attention
to the nature of 'things' and the way that different 'kinds' of 'things' are individuated from—and …

This paper addresses the decomposition of network systems for distributed control. We
construct a novel weighted input–output bipartite graph representation of control systems, in …

This paper presents a high-order graph-based model for an electric vehicle (EV) and
decomposes the model into a hierarchy suitable for use in hierarchical control. The …

The noncentralized model predictive control (NC‐MPC) framework in this paper refers to any
distributed, hierarchical, or decentralized model predictive controller (or a combination of …

Bad error handling is the cause of many service outages. We address this problem by a
novel approach to detect and patch bad error handling automatically. Our approach uses …

To address the complexity challenge of a large-scale system, the decomposition into smaller
subsystems is very crucial and demanding for distributed estimation and control purposes …

Large-scale systems involve a high number of variables making challenging the design of
controllers because of information availability and computational burden issues. Normally …

This paper proposes a distributed model predictive control approach designed to work in a
cooperative manner for controlling flow-based networks showing periodic behaviours …

Community detection decomposes large‐scale, complex networks “optimally” into sets of
smaller sub‐networks. It finds sub‐networks that have the least inter‐connections and the …