Although the effects of climate change are already being felt, global emissions are still rising. In the European Union, heavy- and light-duty trucks are responsible for 39% of CO2 road emissions, while only making up 2.3% of all road vehicles. To meet the CO2 reduction goals set by the European Commission, improving truck volume utilization to lower truck movements is a critical factor. The container loading problem investigates the improvements that can be made in volume utilization. This problem, which is considered to be NP-hard, can be interpreted as a geometric assignment problem in which three-dimensional small items have to be assigned to three-dimensional, rectangular large objects.

While the container loading problem has been studied extensively, existing literature predominantly focuses on maximizing theoretical volume utilization. There is a lack of research on applying volume utilization maximization to large-scale, highly constrained real-world scenarios. Furthermore, there is a lack of studies that provide a trade-off between ideal unloading situations and maximal volume utilization. This gap is bridged in this study by tackling a real-world container loading problem faced by a large e-commerce company. This company transports products in trucks between a distribution centre and multiple local depots, where the products are transshipped to delivery vans. This study investigates whether the current loading of the trucks can be optimized, as this now relies on worker experience rather than algorithmic optimization. Consequently, the company achieves low volume utilization due to existing safety measures and loading using clamp trucks. Furthermore, the company experiences a high number of required handling actions at the local depots to transship the products into the delivery vans. To tackle these challenges, the company would like to investigate the effects on volume utilization of increasing the stacking limit from 2 to 3 and replacing the current loading method with a plate loading method. Also, the company would like to see the effect of the multi-drop constraint on volume utilization. This constraint requires that all items destined for the same delivery van be loaded in the same truck (soft) or together as a group in the truck (hard). This will create better unloading situations at the local depots, but reduce volume utilization.

To bridge the gap between theoretical container loading and a large-scale practical case like the one in this study, a hybrid metaheuristic approach was designed. Initially, a Generic Container Loading Model was developed to solve the basic container loading problem. This model used the Randomized Constructive Heuristic and was validated against the BR1-BR7 dataset, achieving competitive volume utilization. Subsequently, the model was extended to the Case Study Model, which incorporated all the safety measures and other constraints of the company. Here, a hybrid method was used that combined the preprocessing of the Randomized Constructive Heuristic with a Biased Random Key Genetic Algorithm to optimize the sequence of the loaded items.

The model was validated using data on shipped company products over an 8-month period, consisting of nearly 1500 trucks and 160,000 products. This validation demonstrated that the model was capable of simulating the loading process at the company. Scenario-based analysis showed that replacing clamp trucks with a plate loading method and increasing the stacking limit from 2 to 3 can reduce the number of trucks required by 20.98%. Consequently, volume utilization increased from an average of 39.67% to 50.24%. Implementing the soft multi-drop constraint leads to an increase of 8.01% in trucks used, corresponding to a volume utilization of 37.60%. For the hard implementation, the increase in used trucks is 16.67%, corresponding to an average volume utilization of 34.72%. Despite these costs to volume utilization, this study found that implementing a plate loading method and increasing the stacking limit can fully neutralize the increases in trucks used and even provide a slight reduction in trucks used, corresponding to a volume utilization of 41.90%.
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During offshore monopile installation, the crane boom must be lowered onto its boom-rest while the installation vessel remains afloat. This final landing operation is highly sensitive to wave- and wind-induced disturbances, which can excite oscillatory motion of the crane boom about the slewing axis. In severe cases, the disturbances may excite resonant behaviour, leading to uncontrolled boom oscillations. These uncontrolled oscillations compromise the reliability and efficiency of monopile installation, as well as the operational safety of vessel crew members. Boom landing has historically relied on slow manoeuvring and the skill of the crane operator. However, as offshore cranes continue to grow in scale, maintaining safe and reliable operation through manual control alone becomes increasingly demanding under harsh and unpredictable environmental conditions. This thesis investigates whether such oscillations can instead be actively mitigated using the existing slew drive infrastructure, without requiring additional hardware, structural modification or additional manual interference.

In this thesis, a control-oriented dynamic model of the coupled slew drive, slewing platform, and crane boom is developed using the Euler-Lagrange method, capturing the dominant structural flexibility of the boom while assuming small angular deflections. The model is extended with physically derived disturbance inputs representing first- and second-order wave-induced loading and wind loading, based on representative North Sea sea states. Based on this model, a sliding mode controller is designed, in which the sliding surface is formulated to mitigate both the oscillatory and biased components of the boom motion. The switching control component is derived using a physically motivated bound on the combined offshore disturbances, and the resulting design is validated through a Lyapunov-based stability analysis. The controller is implemented and tuned through a combination of theoretical control authority analysis and systematic simulation-based parameter identification. The resulting design is subsequently validated against a realistic lower-level slew drive motor model in Simulink, confirming that the demanded performance is physically possible within the slew drive motor’s bandwidth, speed and torque limitations.

The proposed sliding mode controller substantially reduces slewing-axis oscillations across all evaluated operating conditions. Under nominal offshore operating conditions, representative of typical sea states encountered during monopile installation, the controller reduces the peak boom tip displacement from 0.65 m in open loop to 0.13 m (80.0%). The RMS displacement is reduced from 0.219 m to 0.045 m (79.5%), while the steady-state bias displacement is reduced by 49.3%. Under harmonic excitation at the boom’s natural frequency, the controller achieves its strongest performance, reducing the peak displacement by 94.9%. In all evaluated scenarios, the slew drive motor tracking ratio remains above the required 95% threshold, confirming that the commanded motor speeds are physically realizable by the existing slew drive.

The controller is benchmarked against an existing pole placement controller developed in collaboration with Huisman Equipment. The comparison shows that the sliding mode controller achieves higher oscillation reduction across all evaluated scenarios and excitation frequencies. Compared with the pole placement controller, the sliding mode controller is especially effective at rejecting bias disturbances. However, the pole placement controller requires less control effort and has a more intuitive tuning process and controller structure. Frequency response and sensitivity analyses for variations in the model parameters show that the sliding mode controller is more robust to bounded disturbances and modelling uncertainties.

These results demonstrate that slewing-axis oscillations during crane boom landing can be substantially and reliably reduced through active slew drive compensation by sliding mode control, offering a viable path toward safer, more reliable, more efficient, and less weather-dependent offshore crane boom landing operations. ... Read more

Driven by the need to improve safety, the maritime industry is undergoing a transformative change with the development of autonomous surface vessels, which can aim to reduce the likelihood of accidents by incorporating risk awareness directly into motion planning and control to account for uncertainties in maritime operations. However, existing literature does not consider risk-aware control capabilities that can enable fail-safe actions. To address this limitation, this work proposes a Multi-Trajectory (MT) Risk-Aware Model Predictive Control (MPC) scheme designed to simultaneously optimize two distinct trajectories: a mission-driven nominal trajectory and a fail-safe contingency trajectory. The fail-safe trajectory is computed with a risk cost term in the MPC objective function to guide the vessel towards minimum-risk conditions. In addition, a terminal velocity cost term ensures that the velocity of the vessel can be reduced at each optimization step, to bring it to a near-stop at the end of the fail-safe trajectory. By enforcing a shared initial control input constraint, the system reduces the possibility that the nominal trajectory leads to a state from which an escape is impossible. A supervisory system monitors these trajectories, evaluating them for predicted grounding, the physical capability to bring the vessel to a stop and if the risk is predicted to increase along the nominal trajectory. If a hazardous situation which requires a fail-safe action is detected, defined as a predicted grounding event or a loss of stopping capability while risk is predicted to increase, the supervisory system activates the fail-safe action. The fail-safe action is activated by using the binary variable (B), which accordingly modifies the MT MPC objective function. Verification is performed in a simulation environment by comparing the MT scheme against a Single-Trajectory (ST) MPC scheme during no-fault and stuck rudder and loss of effectiveness fault scenarios in conjunction with drifting forces due to wind. Results demonstrate that the MT scheme is able to able to reduce the likelihood of grounding compared to the ST scheme. Finally, this enhanced safety imposes no penalty on travel time, energy consumption, or path-tracking accuracy during scenarios that do not require a fail-safe action. The only significant trade-off is a two- to three-fold increase in average solver time compared to the ST scheme. ... Read more

Due to poor working conditions caused by emissions, heavy workloads, and significant staff shortages, airlines and airports are turning towards automation for a solution. While many automation developments focus on turnaround management and scheduling, research on the automated execution of turnaround operations is lacking, especially within arrival and departure operations and on the usage of multi-operation vehicles. This study aims to determine whether combining multiple operations into a single autonomous platform is operationally and financially beneficial. Task dependencies and interconnections were modelled, allowing the simulation of interactions and propagation of delays. A financial model was then developed to quantify the impact of changes in turnaround durations on delay-related costs. Based on net present value, reliability, flexibility, and technological readiness, different automated concepts developed for each operation were assessed and compared with multi-operation automated platforms. Additionally, the effects of automation on the scheduling, spatial management, and communications during aircraft turnarounds were analysed, accompanied by a risk analysis. Findings from this study indicate that the automation of arrival and departure operations can provide operational gains and positive financial returns, provided reliability performance meets the required thresholds. Multi-operation platforms enhance flexibility significantly, but may underperform in operational efficiency and financial viability. The results from this thesis provide an informed approach in automating aircraft turnarounds, supporting decision-making on automation concepts and accelerating the transition to an environment that ensures occupational health and safety for ground staff.
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Inland waterways offer a cost-effective, energy-efficient and relatively safer mode of freight transportation, and autonomous navigation presents an attractive opportunity to fully revitalise their utilisation. To enable a safe, efficient and reliable inland waterway ecosystem, autonomous inland vessels must account for uncertainties arising from environmental disturbances and modelling errors. In comparison to open-sea navigation, inland navigation involves confined waterways, frequent interaction with infrastructure and other vessels, and operational constraints that require both high situational awareness and constraint satisfaction. Furthermore, abnormal operating conditions resulting from critical sensor faults and failures must be tolerated through graceful performance degradation or, in the worst case, a fallback operation. In light of these operational requirements, this thesis investigates how autonomous vessels, especially (but not limited to) inland waterway vessels, can maintain safe, high-performance motion control while monitoring sensor faults and hazardous situations that affect their navigation.

More specifically, this thesis contributes an integrated framework that includes (a) a robust system identification methodology to obtain vessel maneuvering models for state estimation and prediction, (b) a Nonlinear Model Predictive Control (NMPC)-based control system that computes the vessel's control actions while satisfying the physical and operational constraints of inland waterways, (c) a multiple sensor Fault Detection and Isolation (FDI) scheme that monitors consistency in measurements by employing analytical redundancy relations and (d) a risk mitigation method that provides a fallback control action under complex failures.

Robust system identification for marine surface vessels

Maneuvering models play a central role in model-based control and monitoring system design by providing accurate estimates of the vessel's states and their future predictions. Identifying the parameters of a full-scale vessel from experimental data is particularly challenging due to significant modelling and measurement uncertainties. The first contribution of this thesis is a set-membership method for identifying key parameters of a nonlinear 3-Degrees of Freedom (3-DOF) vessel model that supports robust prediction and control design through a bounded error characterisation of the uncertainties. The identification process involves computing two sets: a Data-driven Parameter Set (DDPS) and a Feasible Parameter Set (FPS), using the system dynamics, uncertainty bounds and input-output measurements. Then, by solving quadratic programs over the FPS, parameter estimates and their uncertainty bounds are obtained. Validation results from full-scale trials demonstrate improved prediction accuracy and reduced computational time. In addition, through sensitivity analysis, the parameters most crucial for identification performance are identified.

Path-following control of inland waterway vessels in confined waterways

Inland waterways are characterised by tight operational and environmental constraints, leading to explicit control design specifications. The model predictive control methodology is adopted, as it naturally integrates multi-variable dynamics, actuators, state, environmental constraints and objectives to optimise performance and control effort. An NMPC path-following control scheme is proposed for Inland Waterway Vessels (IWVs), with the prediction model tailored to the hydrodynamic phenomena in confined waterways, including bank and shallow-water effects. Many challenging scenarios are considered for validating the control scheme through simulations, such as turning at a steep river confluence, sailing a curved river and avoiding a static obstacle. The impact of reduced ship-bank distances, propulsion speeds and river cross-section shapes further provides insights into control performance and design choices. In addition, key performance metrics are proposed to evaluate the controller's performance and quantify path-following accuracy, robustness and safety.

Multiple sensor fault diagnosis of autonomous surface vessels

Autonomous vessels rely on multiple heterogeneous sensors for navigation, motion control and situational awareness. Sensor faults may propagate through measurements to interconnected systems on board, thereby impacting downstream decisions. This thesis proposes a multiple-sensor FDI scheme that exploits Analytical Redundancy Relations (ARRs) derived from the vessel's dynamical model and adaptive thresholds to diagnose sensor faults.

The design methodology adopted in the proposed scheme includes (a) the generation of fault detection residuals having structural sensitivity to one or more sensor faults and (b) the computation of adaptive thresholds used for residual bounding with robustness against environmental and modelling uncertainties. As a result, false alarms can be avoided in the fault detection process. In addition, a combinatorial fault decision logic is designed, enabling the scheme to not only detect fault occurrence but also to determine the compromised sensors. Combined, the structurally sensitive residuals and the decision logic facilitate the isolation of multiple sensor faults. The proposed fault diagnosis scheme is suitable for continuous monitoring of faults during vessel operation, while easily accommodating variations in the vessel's actuator or sensor configurations. Furthermore, by identifying weak fault sensitivity by evaluating residuals with respect to fault magnitudes, improved fault isolation decisions are obtained.

Collision and grounding risk mitigation of inland waterway vessels

Finally, the risk mitigation of autonomous vessels is explored by considering the underlying sub-problems of risk modelling and control. For risk modelling, a Bayesian Belief Network (BBN) is built from hazard analysis results, providing transition probabilities for sequential decision-making. Thereafter, a Partially Observable Markov Decision Process (POMDP) model is designed to represent the vessel's states and provide a suitable higher-level control strategy that ensures the vessel's safety by preventing hazardous situations, such as grounding and collisions. The method is verified through an inland waterway navigation case study, which demonstrates SCS selection reliably during a complex failure scenario.

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The increasing size of cargo vessels poses significant challenges for ports in ensuring safe mooring, as larger ships result in higher mooring forces.
Most existing port infrastructure and mooring equipment were designed for smaller ships, making accurate estimation of mooring line forces increasingly critical.
Metamodels, machine learning models trained on numerically simulated data, offer a promising alternative to traditional, computationally expensive simulation-based methods by enabling rapid predictions with a useful level of accuracy.
This study proposes a metamodeling approach for the numerical Dynamic Mooring Analysis (DMA) to predict mooring line forces from input parameters that describe environmental conditions, mooring systems, and ship characteristics.
The methodology is demonstrated in a case study involving a 333-meter container vessel moored at a berth in the Port of Rotterdam.
A total of 11,520 scenarios were simulated using the DMA model aNySIM and used to train and test two candidate metamodels: Linear Regression (LR) and Multilayer Perceptron (MLP).
After evaluating both models on predictive accuracy, efficiency in terms of prediction speed and development effort, and interpretability, the MLP was selected as the preferred DMA metamodel.
It achieved high predictive performance, with an RMSE of 10 kN and an R² of 0.996, while offering prediction times measured in microseconds. This is more than seven orders of magnitude faster than the numerical DMA, thereby enabling large-batch predictions.
The metamodel revealed that pretension is clearly the most dominant feature for predicting the mean mooring line force, followed by MBL. For the maximum mooring line force, the most influential features were identified as pretension, windvelocity, and wind direction. ... Read more

Global growth in offshore wind power is creating a shortage of purpose-built cable-laying vessels (CLVs). Retrofitting existing offshore support vessels offers a cost-effective alternative, but these conversions bring together tensioners, carousels and ancillary equipment from multiple vendors that rely on proprietary controls, leaving co-ordination to human operators and voice radio. Manual operation limits precision, scalability and safety at a time when cable-lay tasks are becoming more complex. This thesis responds by designing and evaluating a vendor-neutral integration framework that enables multi-machine automation on retrofitted CLVs.

The research follows a stepwise approach. A literature review first identifies three principal barriers to integration: incompatible communication protocols, intrusive or unreliable sensing and lengthy re-mobilisation after each deck re-layout. From these findings, requirements are derived for an Information and Communication Technology framework that combines robust on-deck tension measurement, modular control logic and real-time data exchange.

A representative case study, consisting of a vertical two-track tensioner and a 375-tonne carousel, is modelled in OrcaFlex and equipped with Proportional-Integral-Derivative controllers. Historical field data are used to tune and verify the model, confirming that simulated tensions, velocities and cable kinematics remain within operational limits.

An OPC Unified Architecture (OPC UA) layer is then integrated as a high-level supervisor to synchronise set points, measurements and alarms. Performance is benchmarked against the verified model using key indicators such as mean-squared error, relative tension error, response time and communication overhead. Results show that OPC UA introduces less than three per cent additional latency and negligible computational load while maintaining co-ordination accuracy under nominal and extreme scenarios. The framework also reduces operator workload from two dedicated operators to one supervisory role and shortens mobilisation time by standardising plug-and-play machine interfaces.

The study demonstrates that retrofitted CLVs can achieve safe, scalable automation through a structured, simulation-verified framework rooted in open standards. The proposed architecture offers a practical pathway towards higher levels of autonomy in offshore cable installation and can be extended to additional machinery or vessel classes with minimal modification. ... Read more

This thesis focuses on enabling safe and reliable navigation for Autonomous Surface Vessels (ASVs) operating in complex and mixed-traffic maritime environments. It presents a suite of motion planning and control algorithms that ensure fault tolerance and compliance with maritime traffic rules, even under uncertainty and component failures. Key contributions include a Model Predictive Contouring Control (MPCC) method that formalizes COLREGs compliance, a model-based fault diagnosis framework using residual analysis, a robust Set-Membership Estimation (SME) approach for fault parameter identification, and a Robust Adaptive Model Predictive Control (RAMPC) scheme that integrates fault information into trajectory optimization. Validated through extensive simulations and implemented in ROS, the proposed framework demonstrates robust performance in dynamic and uncertain conditions, laying the groundwork for real-world deployment of autonomous maritime systems. ... Read more

This thesis presents a COLREG-compliant collision avoidance and detection algorithm for the safe navigation of autonomous surface vessels. The method builds upon the Velocity Obstacle algorithm and implements the concept of the ship domain and the ship arena into the framework. The International Regulations for Preventing Collision at Sea – the COLREGs – are analyzed individually and incorporated in the designed collision avoidance algorithm. The COLREGs were used to determine the preferred passing side and optimized motion for every possible encounter situation with an obstacle vessel. The ship domain and arena help to perform proactive alterations when required, improving on the apparent shortcomings of the VO algorithm. This framework leads to a more proactive collision avoidance algorithm that guarantees COLREG compliance and safe navigation in mixed-traffic environments. The robustness and wide adaptability of the developed algorithm are validated in different encounter situations, ranging from vessel-to-vessel batch simulations to complex, multi-vessel scenarios. ... Read more

As the energy transition progresses and vessel autonomy increases, the control of marine systems is gaining greater significance. This thesis develops safe and resilient control methods for marine Power and Propulsion Plants (PPPs). The proposed methods include fault diagnosis techniques and frameworks for managing the effects of malfunctions and system changes after mission updates, aiming to improve the safety and adaptability of marine PPPs in the evolving maritime industry. ... Read more

During single-blade offshore wind turbine (OWT) installation, wind disturbance results in blade root motion. The sensitivity to this wind disturbance is more significant for larger blades, reducing the allowable installation weather limit. A potential solution is a Hook Mounted Compensator (HMC) between the crane and the load that can provide high-precision compensation across multiple degree of freedom (DOF), and compensate for the influence of wind on the OWT blade. Several Actuation Method (AM)s have been identified that can be used in a HMC. However, these AMs have not been modelled dynamically and their effectiveness for the desired application is unknown. The aim of this study is to analyse and assess the compensation effectiveness of these AMs in a HMC. For this purpose, the AMs are simulated and analysed in various levels of complexity and DOFs. Initially, the system is considered in a 1DOF. A linear representation is formulated, based on which a Proportional-Integral-Derivative (PID) controller for each AM is formulated. This enables simulation of the Single-Blade Installation System (SBIS) in the time domain. Assessment criteria are used to quantify the compensation effectiveness and actuation input of the AMs. To simulate the SBIS for each AM, 3DOF numerical models are developed that describe the operation of the AMs in their respective operational planes. Six actuation methods are included in the assessment. Based on the assessment results, three AMs are combined in a HMC concept. A XY table is used to control blade root position in the x- and y-directions, gyroscopes for the z-direction, and COG shifting with counterweight to prevent gyroscope saturation. The PID controllers based on the linear 1DOF representation are used, operating in parallel, to control the blade root position in all DOF. The blade root motion is reduced by 96% along the blade axis and 86% radially. The blade root motion is sensitive to the mean wind speed, turbulence intensity, and angle of the incoming wind. The HMC shows robustness to variations in tugger line angle and pretension. The static blade pitch angle affects the magnitude and distribution of the wind-induced moment on the blade. For a pitch angle of -180, the moment around the z-axis is minimal, providing optimal HMC performance. The HMC concept can not directly actuate the blade around the z-axis. Instead, the XY table translates the blade at the COG, resulting in increased cylinder stroke and high power consumption for other pitch angles. Two AMs were assessed to actuate the blade around the z-axis, both showing poor performance. Further exploration of AMS that can directly control the blade rotation around the z-axis could lead to improvement of the HMC concept. Additional improvement can be made in optimization of counterweight and gyroscopes sizes, potentially reducing weight and improving system performance. Further suggestions for future work include; exploring the compensating for the now neglected hub motion using the HMC, examining the stability of the HMC once the blade is mated to the hub, and the impact of sensor noise and delay on the HMC’s performance.

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Inland waterway transport is a low CO2 emission alternative to road transport. A shift towards more inland waterway transport could also help reduce road congestion and noise pollution. Infrastructure bottlenecking, particularly at locks, is part of the reasons preventing this shift. Congestion is leading to delays. Locks can be physically improved, or the passage of the vessels through the locks can be optimized through scheduling. Recent work introduced a novel switching-max-plus-linear system approach to scheduling vessels passing through networks of waterways and locks, also introducing a novel routing component to the scheduling problem. Switching max-plus-linear systems are a convenient way to model scheduling systems using max-plus-linear algebra. The switching-max-plus-linear model only considered locks with a single chamber that can only process one vessel at a time. Additionally, it only considered four specific waterway network configurations, rather than any arbitrary network configuration. Real locks can have multiple chambers, and they can process multiple vessels at the same time if they are placed according to regulations in the two-dimensional space of the chamber. The scope of this report was then to build upon this switching max-plus-linear model by adding support for arbitrary network configurations, and multi-chamber, multi-vessel locks with proper twodimensional ship placement, to answer the main research question: How can multi-vessel, multichamber locks with ship placement be integrated into the SMPL IWT scheduling model? Three mathematical scheduling models formulated as SMPL systems were introduced, each subsequent model building on the previous one. The first introduced support for arbitrary network configurations. The second introduced support for multi-chamber locks and allowed vessels to pass through lock chambers at the same time, provided that their assigned one-dimensional sizes fit into the assigned one-dimensional capacity of the chamber. The third introduced support for twodimensional ship placement through a Tetris-like placement sequence also modeled as a switching max-plus-linear system. The models were translated to mixed integer linear programming models, and arrival time and arrival time offset objectives were added, so they could be used as the rules by which a scheduler would build and solve offline scheduling optimization models on a case-by-case basis. Auxiliary objectives to promote vessels slowing down, rather than waiting stationary in the waiting areas, were also added. The models were all found to be working as intended and implemented correctly through the use of a number of verification cases and tests. Complexity tests showed that the solution times for all three models already became larger than a practical limit of 15-20 minutes for simple scenarios with 10-15 vessels. A heuristic model that mimics how vessels are assigned to lockages in practice was built. Comparisons to the scheduling models on the verification cases showed negligible differences for the models in single-lock cases, but it indicated that the multi-vessel, multi-chamber models may outperform practice in multi-lock cases. Future research is recommended to focus on online optimization to account for disturbances, distributed optimization to reduce calculation times, and validation of the model’s performance with real data. ... Read more

Traditionally, the control point (CP) of a dynamically positioned vessel is located around its center of gravity (CoG). However, during offshore operations, other locations, such as the crane tip or gripper position, become more critical due to the load being located there. This thesis proposes shifting the control point from the CoG to an alternative location, specifically the gripper position, to minimize the DP footprint at this location. Minimizing the DP footprint at the gripper location could lead to smaller motion deviations at this critical point. Consequently, this could potentially improve the workability of the vessel, which in turn could lead to higher operational yields. Additionally, the risk of potential damage and unsafe situations offshore is mitigated.

The conventional DP system contains a Kalman Filter, to filter out the first-order motions, a P(I)D controller that calculates the demanded forces to keep the vessel in place, and a thruster allocation algorithm that distributes the demanded forces to all the thrusters in an optimized way.

A new design for a DP system with the control point at the gripper position for the Deepwater Construction Vessel (DCV) Aegir is presented and evaluated. Time domain simulations were performed with the Aegir containing its conventional DP system and with the Aegir containing the newly designed DP system. These time domain simulations were performed using Orcaflex, which contains a model of the Aegir. This model of the vessel is connected to an external Python code, that contains the DP system, including a thruster allocation.


As the new DP system at the gripper location has to cope with coupled equations of motion, it is equipped with a new Multiple-Input-Multiple-Output (MIMO) PD controller, that consists of a decoupling module and separate PD controllers for each DOF. To obtain state estimates for the second-order motions at the gripper location, the state estimates calculated by the Kalman Filter are translated to the gripper location.

The effects on DP performance were assessed by evaluating and comparing the motion responses in the horizontal plane and DP footprint at the gripper location of both models. Also, the thruster behavior and energy consumption of both models are compared. This was done for an incoming wave direction of 135 degrees, a peak period (Tp) of 8 seconds, and significant wave heights (Hs) from 1.0 m to 2.0 m with increments of 0.5 m. The wave spectrum used is a JONSWAP spectrum. As recommended by the classification society, three-hour simulations are performed for the so-called 'base case' sea state with Hs = 1.5m. However, due to the extensive simulation time only one-hour simulations were performed for the cases with Hs = 1.0m and 2.0m.

When comparing the motion responses, one of the most remarkable results is an improved yaw response for the gripper control point model in all sea states that are considered in this study. Further on, the motion responses for sway appeared to be bigger for the gripper control point compared to the center control point in Hs = 1.5m and Hs = 1.0 m. However, the differences in sway are observed to be marginal for Hs = 2.0m.

The results show that the DP footprint has slightly improved in the x-direction for the gripper control point model compared to the center control point model for the base case. The same observation is done for Hs = 2.0m, but the differences found between the models in Hs = 1.0m are marginal. Also, the DP footprint was observed to be slightly larger in the y-direction for Hs = 1.0m and Hs = 1.5m for the gripper control point.

The total thrust outputs as delivered by the DP system during the simulations were converted to power, by using the propeller diagrams (for DP-speed state) for the specific types of thrusters the Aegir is equipped with. From these results, it became clear that the gripper point control model consumes less energy in all tested sea states compared center control point model.

From the results presented in this study, it is concluded that the system itself has potential, but no hard conclusions can be drawn for the system in its current form. Problems were observed with the current thruster allocation algorithm from HES, which need to be explored in more detail and resolved. It is recommended to look into developing a stable working thruster allocation algorithm for both control point models, such that more accurate dynamic simulations can be performed and the system can be assessed under more sea states. ... Read more

Planning rolling stock maintenance based on prognostic data (Condition Based Maintenance, CBM) is a trend since the ideal timing for maintenance before failure can be planned. With the use of prognostics, a failure can be predicted so Corrective Maintenance (CM) can be avoided. Traditional rolling stock decision-making for Preventive Maintenance (PM) is based on the time and/or mileage since last PM routine at the maintenance depot. A sufficient amount of literature is available that considers rolling stock PM planning optimization methods. Planning rolling stock maintenance is constrained by the required availability for passenger operations, the conditions for PM and the maintenance depot capacity. However, the integration of CBM with the rolling stock PM planning has not been researched. CM also needs to be performed and is considered a disruptive element in the maintenance planning. It is expected that integrating CBM in the rolling stock PM planning is less disruptive than CM. This study investigates how CBM impacts the rolling stock PM planning by formulating a deterministic MILP that uses a rolling horizon framework that minimizes the maintenance costs. An approach that optimizes the rolling stock PM planning while being disrupted by unexpected failures that lead to CM is compared with an approach that integrates CBM that is disrupted by predicted failures that can be planned in advance. The outcome of the model demonstrates that CBM is less disruptive to the maintenance planning than CM, because the time to failure gives the model flexibility to find the ideal moment to perform CBM. Conclusions and recommendations of this study can be used for implementing CBM approaches for rolling stock. ... Read more

The Dutch railway network is a dense network with 7000 kilometers of railway tracks spread over only 42,000 square kilometers [1, 2]. Additionally, the railways are responsible for 1.4 million passengers every working day [1]. These factors make both the infrastructure and timetable of the Dutch railway network extremely intricate. On top of that, the number of train trips is expected to grow by 40% by 2040 [3], and with that the complexity of managing the railway network will increase even more.

In the case of conflicts in the timetable, action must be taken to resolve these conflicts in order for train operations to continue. In current Dutch practice, this task resides with train dispatchers. However, it can be difficult for the dispatcher to oversee the situation when multiple trains are involved, and actions taken will have consequences for other trains. This increasingly complex task has resulted in growing interest in so-called Traffic Management Systems (TMS), which are intelligent systems that use conflict resolution algorithms to find solutions to timetable conflicts.

A TMS can be used to support train dispatchers in managing railway traffic. ... Read more

Ship-to-Ship (STS) cargo transfers can significantly improve the efficiency of offshore installations while reducing their associated costs. However, the added complexity of cargo transfers involving ship-mounted cranes at sea poses significant challenges. To address this, crane manufacturers have introduced Relative Heave Compensation (RHC) systems to assist crane operators. Nevertheless, concerns have emerged among installation vessel companies regarding the relative heave measurement systems, which rely on Motion Reference Unit (MRU) sensors placed on both ships. Given that many supplier vessels lack the required sensors and the communication protocols pose bureaucratic hurdles, this research focuses on proposing novel, feeder-independent relative heave measuring solutions. This work introduces two unexplored sensor units, namely the LiDAR-MRU and RADAR-MRU. In the absence of actual sensor data, a simulation workflow using Simulink and Unreal Engine (UE) is presented to generate synthetic data. After, four distinct measurement solutions are developed, implemented, and evaluated using the simulated data in MATLAB. The implemented solutions estimate relative heave distance and speed with a Mean Absolute Error (MAE) ranging from 0.3-5.2% and 0.8-4.3% of the reference's maximum amplitude, and processing times from 1.8-91.4 [ms]. The results underscore their potential for field implementation. However, future validation is needed with actual sensor data. ... Read more

Marine vessels execute many missions during their life cycle, each associated with a different required power profile. The required power is to be provided by the power plant, which has a fixed set of equipment such as diesel engines, generator sets, electric machines, and batteries. Typically, the control of vessel's power plants consist of two levels; a primary level with local controllers for the power plant components, and a secondary level that determines the distribution of the required power to the various components in the power plant. The state-of-the-art only considers a multi-level power plant control architecture assuming a fixed power plant layout, but in practice, the fixed power plant layout may not suffice for generating the power demand dictated by a new mission. This may lead to inefficient use of components, risk of overloading components, or the inability to deliver the required power. To handle this issue, equipment modifications such as additions, removals or replacements would probably be necessary, along with modifications in the multi-level control scheme. To enable the seamless operation of the multi-level plant control system after the modifications is essential for guaranteeing safety and reducing the downtime, which could be achieved by a control architecture that allows for modular use of the power plant components.

This thesis presents the design methodology of a mission-oriented modular control system for marine power plants. To this end, first power profiles, power plant layouts and control systems of multiple vessels such as tugboats, offshore support vessels, cargo ships and cruise ships are analyzed. By decomposing the power profile in two components, the propulsion and auxiliary power demand, the correlation between the power profile of a vessel and its mission is derived, and an algorithm that computes the power profile using mission and vessel data is proposed. Furthermore, the correlation between the power profile and the layout of the power plant is also investigated, with emphasis on how changes in the power profile result in power plant automation modifications. A modular secondary control level is then designed to cope with the required power plant automation modifications, by combining the Equivalent Consumption Minimization Strategy (ECMS) with Supervisory Switching Control (SSC). In this thesis we consider battery modifications, following the example of Wärtsilä's ZESPacks. Simulation results are used to show the performance of the proposed switching control methodology, in relation to the stability of the components in the power plant after automation modifications occur.

The main contribution of this thesis is the novel approach for the secondary level power plant control system, introducing modularity to the otherwise assumed fixed layout of the power plant. Furthermore, the proposed algorithm can be used to determine the expected power profile for a new mission, to identify required modifications of the power plant equipment.
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Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice. ... Read more

Inland waterways form a natural network infrastructure with the capacity for waterborne transport of people and goods for moving freight from seaports to the hinterland. Recently, Inland Waterway Transport (IWT) has been promoted more extensively by the European Union and various governments as it plays a crucial role in reducing road congestion and CO2 emissions from transport. However, the advantages of IWT are not fully exploited due to inefficiencies in the logistics system, such as long waiting times at locks and sub-optimal navigation on waterways. Currently, no scheduling at infrastructures or routing optimisation of the overall waterway network is happening. The scheduling of vessels through a lock is usually performed on a First In First Out basis, providing an opportunity for improvement. Hence, this thesis aims to design a scheduling strategy for generating an optimal plan for sending inland vessels through a waterway network with minimal delays, yielding a significant positive impact on the modal shift towards IWT. 
A promising approach to scheduling problems is by using Switching Max-Plus-Linear (SMPL) systems. SMPL systems have proven to be effective in various Discrete-Event Systems and transportation networks. Using SMPL models is convenient since non-linear scheduling problems can be described linearly using Max-Plus operators without compromising on the system dynamics. Moreover, as the SMPL systems can be transformed into Mixed-Integer-Linear-Programming (MILP) problems, it is also possible to use fast optimisers for solving the scheduling problems.
This thesis will show how one can describe IWT systems, consisting of; waterways, vessels and locks, as SMPL systems. The optimal schedule for the inland vessels is determined based on multiple input parameters, including waterway network lay-out, the sailing speeds of vessels and arrival deadlines of the vessels. The scheduler will return the individual vessel routing and overall vessel order in the waterway network. This routing and order selection is defined using binary control variables, turning the IWT scheduling problem into a MILP problem, which will allow finding the solution to large scale IWT scheduling problems in a reasonable computation time. Furthermore, this thesis will show how the goal of minimising the cumulative arrival times of all vessels in a network can be achieved. This is done for different types of waterway network cases, for which the results are shown and analysed. ... Read more

This research work tries to provide a model-based, distributed Fault Diagnosis (FD) framework that will eventually act as an early warning system for online monitoring of the marine propulsion process, in order to avoid future failures and accidents. Furthermore, the introduction of adaptive thresholds in the monitoring modules of the monitoring agents helps minimize false alarms and reduces the conservativeness in decision-making. Finally, this work comes to provide an integrated sensor and process FD framework that can be adopted on-board marine vessels in the future, and narrow down the gap, regarding FD for marine vessels which is closely linked with maritime safety and maintenance decision-making. ... Read more