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- Dynamic Dependence Among Economic Sectors in Equity Markets(2026) Möller, MarcusThis study investigates the dynamic dependence structure between equity market sectors using a Markov regime-switching copula framework. The analysis focuses on return distributions across economic sectors and their lower-tail dependence, particularly across different market regimes. The proposed model builds on empirical evidence that market drawdowns can be contagious and that pairwise dependence between assets tends to increase during periods of market stress. Modeling dynamic dependence can provide a more robust risk framework for portfolio evaluation and asset allocation. In this setting, dependence is allowed to vary over time through regime shifts and is linked to market sentiment. This thesis extends Bubbles and dependence between international equity markets by Wuyi Ye, Lingbo Gao and Xiaoquan Liu (2024) by applying a similar framework to a different data sample. Specifically, the model is applied to equity market sectors (S&P 500 sub-indices: Industrials, Materials, Energy, Healthcare, Financials, Information Technology, and Consumer Non-Cyclical) rather than a geographic cross section, using daily returns over the period 1989-2026. Empirically, the conditional regime-switching copula provides a better fit for many index pairs than an unconditional regime-switching copula and a static copula benchmark. However, in an out-of-sample asset allocation exercise, we are unable to replicate the economic gains reported in Wuyi Ye, Lingbo Gao and Xiaoquan Liu (2024): portfolios based on the conditional model do not consistently achieve higher riskadjusted returns, evaluated by their Sharpe ratio, than equally weighted portfolios or portfolios constructed using a static copula model. Nonetheless, the model-based portfolios often exhibit lower maximum drawdowns, indicating that the framework can capture and mitigate some tail risk.
- Intermodal Freight Transport on the ScanMed Corridor: Rail-Road-Sea Integration, Efficiency, and System Optimization(2026) Hudugur Sathyanarayana, Karthik; Lies, Emily; Morawetz, Luca; Rodrigues, LuísWith freight transportation being the backbone of economies and preventing a looming climate crisis, a closer look into the modes of freight transportation is needed. To address the economic viability and the environmental impact of a transportation mode, this report compares the transportation costs, the transportation time, and the carbon dioxide emissions of road, rail, and maritime transportation. Policies by the European Union to strengthen the single market incentivize a modal shift of freight transportation from the road to more sustainable modes, including rail transport. Therefore, the European Union has introduced the Trans-European Transport Network (TEN-T). This network consists of essential freight corridors across Europe that shall be strengthened. One of these corridors is the Scandinavian-Mediterranean corridor spanning from Finland across the Scandinavian countries, down to Malta. On this corridor lie Gothenburg and Hamburg with the unique situation of being able to transport freight between these two places by truck, train, or feeder ship. Thus, a comparison between unimodal and intermodal transportation on this stretch is conducted. To take first and last mile logistics into account, transporting a container completely by truck is compared to transporting a container by feeder ship or by train for the main leg and by truck for the first and last mile. Furthermore, a comparison of electric freight systems is undertaken and a proposal to enhance rail freight attractiveness through higher reloading efficiency is explored. The report finds that the best suited mode of intermodal transportation, including first and last mile logistics, is road–rail. It achieves the lowest cost and fastest transportation time for the given route. The most environmentally friendly mode of transportation is the feeder ship, but it has the highest costs and longest transportation time. Furthermore, electrified trains consume approximately 78 % less energy than electrified trucks at this distance. Lastly, an improvement of the reloading efficiency of rail freight could drastically improve its competitiveness.
- Analogue Controlled Active Power Filter for Pulsating Loads(2026) Edberg, Fredrik; Skoog, AxelThis master thesis demonstrates an analogue controlled active power filtration for pulsing load used in radar systems. The main tasks of this thesis was to simulate, design, build and verify a regulation control system on a printed circuit board. This regulation card was connected with a separate power card and should be able to handle 40A pulsed loads without any critical drop in output voltage. The active power filter together with the control card was simulated in LTspice before component selection and a schematic and a layout was designed in KiCad. Then the active power filter with the regulation control system was constructed and verified to make sure it works as intended. The active power filter managed to maintain the output voltage during pulses within a certain limit, dropping to 27.1V, resulting in a viable solution for handling pulsating loads. However, the duty cycle specified of 10% had to be reduced to 9.1% in order to maintain steady state operation due to high transient currents up to 150A during 40A pulses. Improvements, such as a less aggressive control loop and dynamic limits, needs to be implemented to achieve stable operation at higher duty cycle.
- Advanced and Fault-tolerant Control of a BLDC Motor(2026) Torgnysson, Hannes; Martinsson, JohanThis thesis examines the control of a brushless direct current (BLDC) motor used to actuate the park lock and the disengagement clutch in an electric drive unit (EDU) for automotive applications. The primary objective is to enhance the performance of an existing control strategy while developing a complementary open-loop faultdetection method. The motivation for this work stems from opportunities to further improve the existing implementation, where timing inaccuracies during commutation can affect acoustic noise levels and motor smoothness. To address this, the first objective was to improve the existing trapezoidal commutation method by increasing the interrupt frequency from 10 kHz to 15 kHz, thereby enhancing the control system’s temporal resolution. This modification enables more frequent updates to rotor position, commutation states, and pulse-width modulation (PWM) signals, thereby improving control accuracy. Experimental results show that the enhanced method maintains comparable performance at lower speeds while providing smoother operation and reduced noise at higher speeds. The second objective was to develop a sensorless open-loop control strategy that operates the motor without Hall-effect sensor feedback, enabling fault detection when the closed-loop system becomes inoperative due to sensor failure. In this approach, the rotor is first aligned to known positions and then driven through a full mechanical rotation using predefined commutation timing. Overall, the results demonstrate that relatively simple modifications can significantly improve control performance, while the proposed open-loop method offers potential for increased system robustness, although further work is required for practical implementation and validation.
- Robust Adaptive Control of Aerial Vehicles under Significant Model Uncertainty(2026) Tittus, Jared AlexanderControl systems for flying vehicles must satisfy stringent demands for high performance while remaining robust against system uncertainties, such as aerodynamic variations and environmental disturbances. Conventional controllers often face a fundamental trade-off between nominal performance and robustness. This thesis investigates the robustness guarantees and performance of adaptive control methods to mitigate these challenges. The primary focus is the design and implementation of an L1 Composite Model Reference Adaptive Controller. This architecture utilizes a cascade configuration where an outer loop employs direct MRAC to ensure tracking, while an inner loop retains an L1 adaptive structure with a fast predictor to satisfy small-gain stability conditions. The vehicle is modeled as a Linear Parameter-Varying system with decoupled dynamics for roll, pitch, and yaw. The performance of the L1 CMRAC is systematically benchmarked against a conventional Linear Quadratic controller and a standard direct MRAC within a sixdegree- of-freedom simulation environment. Evaluation is conducted across multiple reference paths designed to excite various flight dynamics and cross-coupling effects. To ensure statistical robustness, Monte Carlo simulations are utilized to quantify success rates and tracking accuracy under a broad range of uncertainty conditions. Results indicate that while the baseline LQ controller may achieve a lower rootmean- square error in nominal scenarios, the L1 CMRAC provides a higher success rate and superior robustness under significant perturbations. The analysis further highlights an inherent trade-off within the L1 framework: conservative predictor