Model-based Control of Large-scale Baggage Handling Systems: Leveraging the Theory of Linear Positive Systems for Robust Scalable Control Design

Large-scale baggage handling systems, or large-scale logistic networks, for that matter, pose interesting challenges to model-based control design. These challenges concern computational complexity, scalability, and robustness of the proposed solutions. This thesis tackles these issues in a collection of papers organized in two overlapping parts...

Linear simulation of large scale regional electricity distribution networks and its applications: Towards a controllable electricity network

The volatility of renewable energy sources pose a significant challenge for Distribution Network Operators (DNOs) as it makes planning and maintaining a reliable electricity grid more complex. An essential tool in dealing with the uncertain behavior of renewable energy resources is the load flow simulation, i.e., the standard electricity network...

Control of the doubly-fed induction machine for wind turbine applications

The linear control of doubly-fed induction machines in wind power systems normally encounters the problems in variations of the rotor mechanical angular speed and other time-varying parameters. However, better performance requirements against changes in the machine parameters and exogenous inputs are desired. This can be achieved by appropriate...

Efficient predictive model-based and fuzzy control for green urban mobility

In this thesis, we develop efficient predictive model-based control approaches, including model-predictive control (MPC) andmodel-based fuzzy control, for application in urban traffic networks with the aim of reducing a combination of the total time spent by the vehicles within the network and the total emissions. The thesis includes three main...

Modeling, robust and distributed model predictive control for freeway networks

In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of microscopic traffic models. These macroscopic...

Optimal and Robust Switching Control Strategies: Theory, and Applications in Traffic Management

Macroscopic modeling, predictive and robust control and route guidance for large-scale freeway and urban traffic networks are the main focus of this thesis. In order to increase the efficiency of our control strategies, we propose several mathematical and optimization techniques. Moreover, in the second part of the thesis, based on the hybrid...

Formal Abstractions for Automated Verification and Synthesis of Stochastic Systems

Stochastic hybrid systems involve the coupling of discrete, continuous, and probabilistic phenomena, in which the composition of continuous and discrete variables captures the behavior of physical systems interacting with digital, computational devices. Because of their versatility and generality, methods for modeling, analysis, and verification...

Reverse Stackelberg Games: Theory and Applications in Traffic Control

One of the major challenges in optimization-based control of large-scale intelligent infrastructural networks such as traffic networks is to find efficient multilevel optimization schemes through which decisions can be made by agents or controllers of different interacting layers. The hierarchical game on which this dissertation is focused can...

Model-Based Traffic Control for Sustainable Mobility

Computationally efficient dynamic fuel consumption, emissions, and dispersion of emissions models are developed. Fast and practically feasible model-based controller is proposed. Using the developed models, the controller steers the traffic flow in such a way that a balanced trade-off between the travel times, fuel consumption, and emissions (to...

Efficient model predictive control for large-scale urban traffic networks

Model Predictive Control is applied to control and coordinate large-scale urban traffic networks. However, due to the large scale or the nonlinear, non-convex nature of the on-line optimization problems solved, the MPC controllers become real-time infeasible in practice, even though the problem is solvable in theory. In this thesis, we mainly...

Integrated Control of Mixed Traffic Networks using Model Predictive Control

Motivation The growth of our road infrastructure cannot keep up with the growing mobility of people, and the corresponding increase in traffic demand. This results in daily congestion on the freeways. It is an illusion that the problem of congestion can be solved completely within a few years, but it is possible to improve the current situation....

Model-Based Control for Postal Automation and Baggage Handling

In this thesis we focus on two specific transportation systems, namely postal automation and baggage handling. Postal automation: During the last decades the volume of magazines, catalogs, and other plastic wrapped mail items that have to be processed by post sorting centers has increased considerably. In order to be able to handle the large...

Traffic management and control in intelligent vehicle highway systems

Traffic congestion is a problem experienced daily by most of us. Among various traffic management schemes, efficient utilisation of the existing roadside infrastructure combined with in-vehicle technologies offers a promising solution to address traffic congestion and related problems. This approach has resulted in the development of Intelligent...

Multi-Agent Look-Ahead Traffic-Adaptive Control

The objective of this thesis is to create a distributed, multi-agent, approach to traffic control. This PhD thesis' focus is on the control of a network instrumented by traffic signals.A thorough literature study has been performed, reviewing the current state of the art in traffic signal control. On the basis of this literature survey, a...

Multi-agent model predictive control with applications to power networks

Transportation networks, such as power networks, road traffic networks, water distribution networks, railway networks, etc., are the corner stones of our modern society. As transportation networks have to operate closer and closer to their capacity limits and as the dynamics of these networks become more and more complex, control of these...

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...

Model Predictive Control for Integrating Traffic Control Measures

Dynamic traffic control measures, such as ramp metering and dynamic speed limits, can be used to better utilize the available road capacity. Due to the increasing traffic volumes and the increasing number of traffic jams the interaction between the control measures has increased such that local control measures are often not sufficient anymore....