System identification has been widely applied in various engineering fields. In most existing approaches, healthy data are required to first identify the system model, which then serves as the basis for controller design and fault analysis. However, in practice, system dynamics may change over time, and healthy data are not always available. Therefore, how to perform system identification using only faulty data remains an important research direction.

In the field of fault handling, fault estimation has attracted increasing attention in recent years. Compared with fault detection and isolation, fault estimation aims to determine the magnitude and temporal profile of the fault signal. Nevertheless, many existing fault estimation methods assume that faults can be modeled either as actuator faults or sensor faults. In practice, however, many faults cannot be accurately categorized into these two types.

In this thesis, we investigate how to simultaneously perform system identification and fault estimation for LTI systems using only faulty data. Without assumptions about fault types, a feasible subspace containing the true system matrices can be estimated using recent results. However, identifying the true matrices from this feasible set while simultaneously estimating the fault signal remains an unresolved problem.

In this thesis, we address this problem by assuming that the fault signal can be represented using elements from a predefined fault dictionary. We show that under certain conditions, accurate system identification and fault estimation can be achieved. We further propose an algorithm for cases in which these conditions are not satisfied.
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This thesis presents the design and implementation of a process monitoring system for the HIsarna pilot plant aimed at the early detection of anomalies, specifically foamers. Though rare, foamers represent severe process faults that can significantly impact the plant’s safety and reliability. Early detection of these events is crucial for maintaining operational stability.

Given the ambiguous definitions of nominal and non-nominal operations in HIsarna, this thesis constructs a precise definition based on foamer characteristics. Foamers are non-nominal operations, while the absence of these foamer characteristics indicates nominal operations. The monitoring system utilizes data from a gas analysis sensor in the plant’s topside outlet, the dogleg. The dogleg gas analyser is chosen for its reliability and the absence of monitoring methods based on this sensor. To ensure the accuracy of the sensor data, an optimizationbased method is employed to eliminate air ingress disturbances.

An anomaly detection method based on distance measures is developed, incorporating the HIsarna Operation Model (HIOM) to reduce sensitivity to operating point changes. Historical process data is analyzed to establish a distance measure that reflects the correspondence of current measurements to nominal operations. The performance of the anomaly detector is evaluated based on the number of foamers detected, hours per false alarm, and detection time.

The primary contribution of this thesis is the development of an anomaly detection algorithm using Mahalanobis distance for the HIsarna pilot plant. This metric indicates how closely current measurements match historical nominal operation data. Additional contributions include a rigorous definition of nominal and foaming operations, an optimization-based method for air ingress removal, and an observer for dogleg gas analysis data, which can estimate carbon conversion and oxygen flow prediction bias of HIOM. ... Read more

This research presents the design and implementation of a fault diagnosis filter for a high-fidelity simulation model of the AB383 wire bonder. Fault diagnosis, which consists of detecting, isolating, and estimating faults, enables more effective maintenance strategies and potentially mitigates costly downtime in high-precision motion and positioning systems. When a system deviates from its expected behavior, it can be an indication of the presence of a fault within the system. Faults can occur as either multiplicative faults, arising from deviations in parameters within the system, or additive faults, resulting from external fault signals that impact the system’s operation. This study uses a model-based methodology that generates residuals that are subsequently analyzed using a regression method aimed at determining the influence of each fault in the residual signal, thereby facilitating fault estimation. A residual signal represents the difference between the actual system behavior and the expected behavior, mainly serving as an indicator of potential faults within the system. A data-driven threshold design is proposed to determine the detectability of faults. The main contributions of this work include the development of a fault modeling framework for the residual generation method and the application of the fault estimation framework to a linear high-fidelity simulation model affected by both multiplicative and additive faults. The simulation results demonstrate satisfactory performance, that is, accurately detecting and estimating faults. Moreover, the proposed method effectively identifies external disturbances and high levels of noise through power spectral density analysis. The findings highlight the potential of this approach, outperforming alternative methods in terms of accuracy when it comes to fault diagnosis for wire bonder machines. The research findings contribute to the active field of fault detection and estimation for complex systems, offering valuable insights for further studies and potential practical applications. ... Read more

For this thesis we have compared communication times of different control schemes on a wireless control network for a water irrigation system. Therefore a control application which can run different protocols was created. We have shown that a significant reduction of communication time can be achieved by using event-triggered control (ETC), and by using self-triggering techniques we could reduce this even further. Wireless control networks (WCN) are networks of one or multiple controllers, sensors and actuators which share a digital communication network. Sensors send their measurements to the controller, and the controller sends a control signal to the actuators. Because the nodes are digital devices, periodic control is the standard approach. Communication therefore is not needed all the time, and nodes can sleep in between updates to save energy. Event-triggered control is a technique to further reduce communication of resource constrained nodes in the network by only updating control when an event, typically a significant change since the last control update, occurs. Water irrigation systems (WIS) are networks of channels transporting water from main rivers, to smaller rivers which need to be controlled to avoid losses. At TU Delft a model of a water irrigation system with three pools has been connected to a WCN to simulate this. To create an application for this testbed, supporting different control schemes, a low power embedded OS capable of doing multitasking with a replaceable network stack is needed. The Contiki Operation System is capable to do this and has been used by the D3S Research Group of the University of Trento to build wireless control bus (WCB), and has also been used for the WIS control application. WCB uses network floods from a protocol called Glossy and a schedule to synchronise communication with low power, and supports both periodic and event-triggered control. Experiments with WCB show periodic control is possible with only 7% communication time for this setup, and event-triggered control with only 2% without much loss of performance. Because the testbed unit has some technical problems, a hardware-in-the-loop simulation was created to connect to the WCN to do the experiments. A further reduction in communication has been achieved by combining a predictive control method called PSTC with ETC, which we call ETC+. Advantages over normal ETC are not large in our experiments, and there are still practical problems, but they show this is a promising research area. ... Read more

The application of optimal control structures for water irrigation systems (WISs) can be enabled by applying wireless event-triggered control (ETC). The term WIS, is used to describe open-water channels, that are mainly used to supply water to farmers all around the world. The water levels in these channels need to be controlled, but because of the large scale of WISs, it is very expensive to create centralized control structures when using wired connections between individual sensors, actuators and a centralized controller. Previously, WISs were typically controlled using individual decentralized (non-communicating) controllers. Applying wireless technologies enables communication between (smart) sensors, actuators and a centralized controller without the expense of installing and maintaining cables over lengths of kilometers. To create such a wireless infrastructure, a network needs to be designed, consisting of multiple nodes that are able to communicate with each other over wireless. Each sensor and actuator will be connected to (or integrated in) a node, just like the centralized controller needs to be connected to a node. To minimize the costs related to creating such an infrastructure, the nodes should have their own power source in order to prevent that a maintenance worker has to change the batteries of the nodes periodically. The nodes could be powered using a solar panel, or by using energy harvesting, which could be done by using a turbine to extract energy from the flow in a water channel. When using such energy sources, it is important to minimize the power consumption of the nodes. Most of the consumed power is used in communication when transmitting information. By applying ETC, the amount of communication between the individual parts of the control system is minimized, while still retaining good closed-loop system control using a centralized controller. In this research, techniques on wireless control, ETC and WIS control are combined and the application of an event-triggered centralized controller is presented using simulations, as well as the achievable reduction in communication compared to regular periodic control. Furthermore, a cyber-physical lab setup is designed and built which makes it possible to test these techniques in the Delft Center for Systems and Control (DCSC) lab. ... Read more

With the recent development of control systems, event-triggered control (ETC) has been introduced to prevent unnecessary usage of resources, which often happens under time-based control implementations. This thesis presents a novel approach to periodic event-triggered control (PETC) that aims at reducing the number of transmissions between the controller and the sensors even further. This goal is particularly important in networked control systems (NCSs), where communication and computation resources are scarce. In this report, a relaxed triggering condition is introduced that relies on bounding the Lyapunov function of the continuous-time closed-loop system with an exponentially decaying function, rather than requiring its monotone decrease. The relaxed PETC achieves significantly less transmissions compared to existing PETC implementations. The thesis pushes the limit of event-triggered
control even further, by introducing an algorithm for a scheduler of NCS that allows to skip some of the events. This can be seen as a ‘last resort’ approach, that postpones the transmission as much as possible. It is inspired by methods used in self-triggered control (STC) and scheduling event-based NCS. Reducing the communication between the plant and the controller introduces some trade-offs that are also discussed in this report. Finally, several modifications of presented ideas are given that can be applied depending on the main objectives
on the performance of the control loop. ... Read more