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Research ENTEG Smart Manufacturing Systems


30 August 2022: defense Monica Rotulo: "Results on data-driven controllers for unknown nonlinear systems"

Promotores: Prof Claudio De Persis and Dr Pietro Tesi

30 April 2021: defense Mark Jeeninga: "DC power flow feasibility for constant-power loads:

Promotores: Prof C. De Persis and Prof Arjan van der Schaft


This thesis looks into direct current (DC) power grids, both on a small scale and large scale. These networks usually consist of loads and sources.

When a load tries to demand too much power from the grid for a long time, it may happen that the voltage over the load promptly decreases, which can result in a blackout. The cause of this event is that the sources in the power grid cannot transport enough power to the loads. This thesis unravels the exact conditions under which the demands of these loads can be satisfied. The theoretical limits of these DC power grids are described, along with cases for which there is a "simple" guarantee that the transport problem can be solved. This thesis also thinks about guarantees for this solvability in the situation where DC microgrids are interconnected, and about the influence of uncertainties in power lines on this transportation problem.

IEEE Outstanding paper award for Cucuzzella et al.

15 January 2021

IEEE Transactions on Control Systems Technology Outstanding Paper Award, for “A Robust Consensus Algorithm for Current Sharing and Voltage Regulation in DC Microgrids”, by M. Cucuzzella, S. Trip, C. De Persis, X. Cheng, A. Ferrara, A. van der Schaft, in TCST, vol. 27, no. 4, pp. 1583-1595, July 2019. This award recognizes the paper’s originality, relevance of the application, clarity of exposition, and demonstrated impact on control systems technology. The award has been presented virtually during the Control Systems Society Awards Ceremony at the 2020 IEEE Conference on Decision and Control.


20 November 2020: defense Henk van Waarde: "From data and structure to models and controllers"

Promotores: Prof Kanat Camlibel and Dr P. Tesi

Systems and control theory deals with analyzing dynamical systems and shaping their behavior by means of control. Dynamical systems are widespread, and control theory therefore has numerous applications ranging from the control of aircraft and spacecraft to chemical process control. During the last decades, a series of remarkable new control techniques have been developed. The majority of these techniques rely on mathematical models of the to-be-controlled system.
However, the growing complexity of modern engineering systems complicates mathematical modeling. In this thesis, we therefore propose new methods to analyze and control dynamical systems without relying on a given system model. Models are thereby replaced by two other ingredients, namely measured data and system structure.
In the first part of the thesis, we consider the problem of data-driven control. This problem involves the development of controllers for a dynamical system, purely on the basis of data. We consider both stabilizing controllers, and controllers that minimize a given cost function.
Secondly, we focus on networked systems. A networked system is a collection of interconnected dynamical subsystems. For this type of systems, our aim is to reconstruct the interactions between subsystems on the basis of data.
Finally, we consider the problem of assessing controllability of a dynamical system using its structure. We provide conditions under which this is possible for a general class of structured systems.

25 October 2019: defense Mingming Shi: "Coordination networks under noisy measurements and sensor biases"

Promotores: Prof. C. De Persis and Prof. P. Tesi,

Time: 12.45
Location: Aula Academy building

Large scale network systems have been constructed and utilized to provide services ranging from energy acquisition and water distribution to health monitoring and transportation. The operation of these complex systems relies on sensors and actuators to acquire and control the system states, which are commonly exchanged among the sub-parts of the systems via communication channels, due to the spatial separation of the systems. Considering the pervasiveness of these man-made complex systems and the importance of the data extraction and exchange, attention should be paid in understanding how large scale systems behave when there are uncertainties in the measurements and communications. Aside from transmission delays and information missing, noise is also a major issue in data exchange. In addition, when sensors are used to measure variables, the problem that arises commonly is that the read-out may not be exactly equal to real value. In both cases, the data error prevents the systems to get accurate state information. As the current emergence of Internet of Thing, Industry 4.0, smart city and 5G, sensors and communication mediums are playing more and more important roles in network systems. Considering these facts, this thesis focuses on analysing and addressing the issues in network systems caused by the error in state measurement and exchange. We first consider two algorithms to deal with the data exchange error, with a particular interest in designing robust network coordination algorithms against unknown but bounded communication noise. In chapter 3, we propose a self-triggered consensus algorithm to tackle the state drift problem of consensus dynamics caused by the communication noise. In chapter 4, we refine the resultby proposing a different algorithm. Although these two algorithms both can achieve practical consensus and guarantee boundedness of system state, the mechanisms of them are different. The first algorithm relies on an adaptive threshold, which is adjusted based on the node state, to zero the control inputs of the nodes when their disagreements are sufficiently small. The second algorithm imposes the bound on the state of each node by saturating the state received from the node neighbours. Lastly, we consider the state measurement error, and focus on estimating the sensor bias from the incorrect measurement. The sensors in the network measure the relative states of their neighbours, and the measurements may contain biases. We discuss the conditions of the measurement graphs and the number of biased sensors that allow the biases to be reconstructed from the measurements. Furthermore, we provide distributed algorithms to compute the value of the biases.

12 July 2019: defense Tobias van Damme: Thermal-aware job scheduling in data centers. An optimization approach.

Promotores: Prof C. De Persis and Dr P. Tesi

Data centers are becoming more and more vital for every day life: they are huge computational beasts that run google queries, keep facebook profiles, and store our data in the cloud. As a result, research has focused the last decade on making the computing halls that host data centers more energy efficient. This thesis focuses on thermal management and control techniques that balance the thermal load in the data center, using knowledge of the thermal flows and leakages among the server equipment. For maximal utility, the controllers are extended to allow operation at the operating boundary.
The results are completed by simulating a combination of thermal-aware controllers designed in this thesis, and power-aware controllers designed elsewhere. It is shown that a smart combination of both techniques results in greater energy reductions than implementing a single-purpose controller. Finally this thesis provides a method for characterizing the thermal map of any data center. With this identification method, it is possible to apply the controllers designed in this thesis to any existing data center.

7 December 2018: defense Tjerk Stegink: Energy-based analysis and control of power networks and markets. Port-Hamiltonian modeling, optimality and game theory.

Promotores are: Prof De Persis and Prof van der Schaft

Time: 12:45PM

Location: Aula Academy building

30 November 2018: defense Danial Senejohnny: Resilience of coordination networks: data availability and integrity

Promotores: Prof C. De Persis and Dr P. Tesi

With the advent of new concepts like Internet of Things (IoT), Industrial 4.0, Smart Cities, Smart Grid, new opportunities are brought into several industrial and societal domains ranging from transportation and electric power generation to traffic flow management and health care. Many of the above mentioned sectors and industries are essential to the health, safety, and security of our society and are considered critical infrastructure. This emphasizes the importance of rendering such systems “resilient” against malfunctioning due to genuine failures or cyberattacks.
Real-time availability and integrity of data are crucial to ensure normal operation of the system. The first factor is related to to the fact that data flow can be occasionally interrupted, while the second factor is related to the fact that the data content might be corrupted. Given these important factors, this thesis investigates the problem of designing coordination protocols over digital communication channels, which are resilient against the lack of data and unreliable information. The results are divided in two parts.
Part I is concerned with resilience against the absence of data and information accessibility due to genuine failure or cyberattacks, which results in Denial-of-Service (DoS). In particular, we are concerned with jamming attacks as we are mainly interested in wireless sensor networks. We design resilient consensus and synchronization protocols for both shared and peer-to-peer communication networks.
Part II is concerned with resilience against unreliable information in the network which could be the result of genuine fault/error in the control system operation or cyberattack. The nodes that communicate untrustworthy data in the network are considered misbehaving. We investigate a resilient consensus protocol against several type of misbehavior resulting from error in operations such as, data acquisition, data transmission, control logic, and update time scheduler.

10 July 2018: defense Erik Weitenberg: Control of electrical networks: robustness and power sharing

Promotores: Prof C. De Persis and Dr P. Tesi

Time: 11.00
Location Aula Academy building

Thanks to technological and societal developments, the power network as we know it is changing at a rapid pace. On one hand, as more and more people demand green energy, the supply of power becomes more volatile, as it increasingly depends on sunlight, wind and other factors. On the other hand, the advent of e.g. smart consumer electronics and vehicles with large batteries in theory allows the network to absorb this volatility. This book introduces control algorithms to do so, and ways to quantify to what extent such controllers are indeed effective and safe. The first part focuses on two existing control algorithms for the alternate current power network, the distributed averaging integral controller and the leaky integral controller. It introduces a way to measure how quickly a power network that uses one of these controllers is able to recover from disturbances, and consequently, to what extent a controlled power network can withstand adverse conditions, like measurement errors and attacks on the controllers' communication network. The second part introduces new control algorithms for direct current networks. These networks are in current use, for example on ships, and are also suitable for powering micro-grids: small-scale networks that can operate independently of the rest of the power network. These control algorithms make sure the power network is stable, and additionally, fairly distributes the power demand among the generators.

6 October 2017: defense Tjardo Scholten: Control of flow networks with constraints and optimality conditions

Promotor: Prof C. De Persis

More than 40% of the total consumed energy is used for space heating and most of it is generated form fossil fuels. Fortunately there is a shift towards more sustainable sources such as geothermal energy, waste heat and heat pumps. However the supply of these heat sources can be intermittent and is often not co-located with the demand. For this reason a district heating network with storage capabilities can be used for the transportation and security of delivery. A downside is that some heat dispersion occurs in the transportation pipes. This dispersion can be lowered when smaller pipes are used, but this increases the friction in the pipes. To overcome this, the number of pumps in these networks can be increased.

Due to the extra pumps and the introduction of multiple producers that are not nessecarily owned by the same entity it follows that the next generation of heat networks require new control strategies in which communication is crucial. In this thesis we design and analyze such control strategies to optimally coordinate the generation and regulate the storage levels such that the heat supply can be guaranteed. In order to guarantee scalability, avoid a single point of failure and minimize the information that companies need to share, we suggest a distributed mechanism that uses a peer-to-peer communication network. We also design controllers that can regulate the pressure in a network with multiple pumps. As these pumps can often only generate positive pressures we guarantee that this constraint is satisfied.

6 October 2017: defense Sebastian Trip: Distributed control of power networks. Passivity, optimality and energy functions

Promotor: Prof C. De Persis

Social and technological developments resulted in an increase of electricity demand, generated by an ever increasing amount of renewable energy sources. Despite its potential benefits, a continuation of these developments poses significant challenges to the planning and operation of the existing power networks. An important operational aspect in power networks is the regulation of its frequency, which is the focus of this work.
In the presence of more and smaller generation units, careful coordination among the individual parts in the power network is needed, ensuring proper overall functioning. We design and analyse distributed controllers, that ensure that actions taken by local controllers are consistent with global optimality objectives, such as the minimization of generation costs. The total energy of the power network plays a major role in this process, enabling the derivation of useful system theoretic properties without detailed knowledge of all components. Particularly, this work shows that energy functions are suitable to derive passivity properties of various nonlinear power system models, that form an excellent staring point for the controller design. Proposed controllers are shown to regulate the frequency and to obtain an economic dispatch.
We show that it is, although challenging, of importance to incorporate the generation side and the communication network explicitly in the design phase of controllers and that neglecting these aspects can result in an unjustified belief that stability of the network is guaranteed by suggested solutions.

26 Juni 2015: defense Matin Jafarian: Coordination with binary controllers. Formation control and disturbance rejection.

Promotores: Prof C. De Persis and Prof J.M.A. Scherpen

Distributed formation keeping control is a motion coordination problem which aims at achieving a desired geometrical shape for the positions of a group of agents (e.g. robots). In problems of formation control, an important component is the flow of information among the agents. Although the usual assumption in the literature is the exchange of perfect information among the agents, the latter might be a restrictive requirement due to real-world constraints. To cope with this restriction, quantized information and control have been proposed and studied in the literature. In particular, there has been a growing interest in binary quantizers and controllers owing to the recent developments in cyber-physicalsystems. This thesis is mainly focused on the problem of distributed position-based formation keeping of a group of continuous-time dynamic agents using binary controllers. The binary information and control models a sensing scenario in which each agent detects whether or not the components of its current distance vector from a neighbor are above or below the prescribed distance and applies a force (in which each component takes a binary value) to reduce or increase the actual distance. In this context, we consider different classes of dynamical agents, including strict output passive systems, unicycles, and nonholonomic wheeled carts. For the control design and analysis, we use tools from discontinuous dynamical systems, passivity, hybrid dynamical systems, graph theory and internal-model-based approach.

Laatst gewijzigd:08 juli 2022 15:12