Enabling Hybrid Distributed Model Predictive Control of Traffic Signals In Urban Arterial Networks: An on-street application in industry

Road users still encounter unnecessary delays due to inefficient traffic control in urban traffic networks. These delays are ever-increasing and have large environmental and economic consequences. In the Netherlands, most intersections are controlled using actuated controllers, which respond directly to the current traffic demand obtained from...

Model-based control for hybrid and uncertain smart energy systems

Energy systems influence many aspects of society, from the residential sector to the commercial one. Improving the performance and efficiency of energy systems and guaranteeing their stability is a fundamental task of control engineers. In this regard, this thesis presents modeling and control solutions for energy systems, with a focus on both...

Multi-agent control of urban transportation networks and of hybrid systems with limited information sharing

This thesis aims at developing efficient methods for control of large-scale systems by employing state-of-the-art control methods and optimization techniques. This thesis is divided into two parts. In the first part, we address dynamic traffic routing for urban transportation networks. In the second part, we address multi-agent model predictive...

Model predictive control for Max-Plus-Linear and piecewise affine systems

This Ph.D. thesis considers the development of new analysis and control techniques for special classes of hybrid systems and discrete event systems. Two particular classes of hybrid systems (piecewise affine systems and max-min-plus-scaling systems), and two particular classes of discrete event systems (max-plus-linear systems and switching max...

Multi-agent model predictive control for transportation networks with continuous and discrete elements

For several reasons, control of transportation networks like road traffic networks, power transmission networks, water distribution networks, etc. has to be done using a multi-agent control approach. We consider a multi-agent control approach in which each control agent uses Model Predictive Control (MPC) to determine its actions. Each control...