Development of a Python tool based on model predictive control for an optimal management of the Calais canal

Model predictive control (MPC) has been widely employed to control a large variety of water systems, such as dams, irrigation canals, inland waterways, drinking water networks and wastewater treatment plants. Its predictive capabilities and the possibility to incorporate constraints make MPC well suited to address several, and sometimes...

Observer-based robust control for dynamic positioning of large-scale heavy lift vessels

With the growing demand of large-scale heavy lift vessels in the deep-sea offshore construction works, high performance of Dynamic positioning (DP) systems is becoming ever crucial. However, current DP systems on board of heavy lift vessels do not consider model uncertainty (typically arising from mooring forces). In this paper, an observer...

Recursive Kronecker-based Vector AutoRegressive identification for large-scale adaptive optics

This brief presents an algorithm for the recursive identification of Vector AutoRegressive (VAR) models of large dimensions. We consider a VAR model where the coefficient matrices can be written as a sum of Kronecker products. The algorithm proposed consists of recursively updating the Kronecker factor matrices at each new time step using...

A distributed networked approach for fault detection of large-scale systems

Networked systems present some key new challenges in the development of fault-diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect...

Time-Varying Scheme for Non-Centralized Model Predictive Control of Large-scale Systems

The Non-Centralized Model Predictive Control (NC-MPC) framework refers in this paper to any distributed, hierarchical, or decentralized model predictive controller (or a combination of them) the structure of which can change over time and the control actions of which are not obtained based on a centralized computation. Within this framework, we...

Computing in Large-Scale Dynamic Systems

Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data dissemination are challenging to operate and thus...

Coordination in urban water supply networks using distributed model predictive control

Urban water supply networks are large-scale systems that transport potable water over vast geographical areas to millions of consumers. A safe and efficient operation of these networks is crucial, as without it living in today’s cities would be impossible. To achieve an adequate operation, these networks are equipped with actuators like pumps...

Coordinated model predictive reach control for irrigation canals

Irrigation canals are large-scale systems, covering vast geographical areas, and consisting of many interconnected canal reaches that interact with control structures such as pumps and gates. The control of such irrigation canals is usually done in a manual way, in which a human operator travels along the irrigation canal to adjust the settings...