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Recent Submissions
Data-Driven Predictive Control: Equivalence to Model Predictive Control Beyond Deterministic Linear Time-Invariant Systems
(University of Waterloo, 2025-02-07) Li, Ruiqi
In recent years, data-driven predictive control (DDPC) has emerged as an active research area, with well-known methods such as Data-enabled Predictive Control (DeePC) and Subspace Predictive Control (SPC) being validated through reliable experimental results. On the theoretical side, it has been established that both DeePC and SPC methods can generate equivalent control actions as one can obtain from Model Predictive Control (MPC), for deterministic linear time-invariant (LTI) systems.
However, similar results do not yet exist for the application of DDPC beyond deterministic LTI systems. Therefore, the objective of our research is to generalize this theoretical equivalence between model-based and data-driven methods for more general classes of control systems.
In this thesis, we present our contributions to DDPC for linear time-varying (LTV) systems and stochastic LTI systems. In our first piece of work, we developed Periodic DeePC (P-DeePC) and Periodic SPC (P-SPC) methods, which generalize DeePC and SPC from LTI systems to linear time-periodic (LTP) systems, as a special case of LTV systems. Theoretically, we demonstrate that our P-DeePC and P-SPC methods have equivalence control actions as produced from MPC for deterministic LTP systems, under appropriate tuning conditions. As an intermediate step in our theoretical development, we extended certain aspects of behavioral systems theory from LTI systems to LTP/LTV systems. This includes extending Willems’ fundamental lemma to LTP systems and the defining the concepts of order and lag for LTV systems.
In our second piece of work, we proposed a control framework for stochastic LTI systems, namely Stochastic Data-Driven Predictive Control (SDDPC). Our SDDPC method theoretically achieves equivalent control performance to model-based Stochastic MPC, under idealized conditions of appropriate tuning and noise-free offline data. This method, which applies to general linear stochastic state-space systems, serves as an alternative to the data-driven method previously proposed by Pan et al., which also achieved theoretical equivalence to Stochastic MPC but was limited to a narrower class of systems. Beyond the theoretical assumption of noise-free offline data, we performed our SDDPC method in simulations with practical noisy offline data. The simulation results demonstrated that our SDDPC method outperforms benchmark methods, achieving lower cumulative tracking cost and lower rate and amount of constraint violation.
Transition metal doped ceria catalyst prepared by direct precipitation method for thermocatalytic conversion of carbon dioxide via reverse water gas shift
(University of Waterloo, 2025-02-05) Xia, Wenxuan
Since the beginning of the industrial revolution, mankind has utilized large amounts of fossil fuels to obtain energy, which has led to the emission of large amounts of greenhouse gases such as carbon dioxide. How to reduce CO2 and utilize CO2 to obtain high-value products has become a hot topic in today's research. The thermocatalytic reduction of CO2 by using renewable H2 is expected to be a potential solution to these challenges.
In this experiment, the reverse water gas shift (RWGS) reaction of various loaded transition metal doped cerium (MCeO2) catalysts (M = Fe, Co, Ni and Cu) was investigated. The desired catalysts have been synthesized by utilizing the direct precipitation method. The reverse water gas shift reaction has been extensively studied including reaction tests and some characterizations such as X-ray crystallography (XRD), Brunauer Emmett Teller (BET), Temperature Programmed Desorption (TPD), Inductively coupled plasma - optical emission spectrometry (ICP - OES) etc.
In reaction tests, the performance of M-CeO2 was evaluated in terms of conversion and selectivity by varying the temperature (400°C - 600°C). The resulting reaction products were monitored using an on-line infrared analyzer to identify the formation of carbon monoxide (CO), methane (CH4), and unconverted CO2. T-test results show that transition metal doping has a significant effect in enhancing the surface CO2 adsorption and reduction. effects, including high loading of Fe with higher than 56% CO2 conversion and 100% selectivity to CO at 600 °C, Cu with 100% selectivity to CO but lower CO2 conversion, and Co and Ni with significant methanation ability, especially at high loading.
In addition, the structures of the catalysts before and after the reaction were investigated using XRD. The binding strength of CO2 on the doped CeO2 surface was investigated using the programmed temperature rise desorption (TPD) method. The effect of specific surface on CO2 adsorption was investigated using BET.
This experiment explores the effect of different kinds of transition metal-doped cerium catalysts on the reverse water-gas shift (RWGS) reaction, which reduces excess CO2 emissions and also provides an idea for CO2 conversion and utilization.
The Great Migration, Urban Spatial Structure, and Their Economic and Environmental Impacts in the U.S.
(University of Waterloo, 2025-02-05) Shen, Zixing
This thesis investigates the transformative impact of the Great Migration on urban spatial structure in the United States and its subsequent economic and environmental consequences. The Great Migration (1910-1970), marked by significant African American migration from the South to Northern and Western cities, reshaped the demographic and spatial landscape of receiving cities. Yet, the long-term spatial dynamics and their implications remain underexplored, a gap this study aims to address.
Using a novel dataset constructed through the City Clustering Algorithm (CCA), this research redefines historical urban boundaries, creating “synthetic cities” (Syncities) that more accurately reflect urban development from 1900 to 1970. The analysis reveals how demographic shifts influenced the size and shape of cities, with implications for their economic performance and environmental quality. By employing instrumental variable regression and mediation analysis, this thesis identifies the causal pathways through which these spatial transformations affected income levels and air quality, both immediately following the migration and decades later.
The findings highlight both economic growth and environmental challenges linked to urban expansion. Cities with larger and more dispersed urban forms benefited economically in the short term but faced greater environmental degradation over time. These results underscore the importance of urban spatial structure in shaping sustainable development trajectories.
By bridging historical demographic changes with contemporary urban outcomes, this study offers valuable insights for urban planning and policy, demonstrating how historical conditions continue to shape modern challenges. This work also provides a methodological foundation for future research on the interplay between migration, urban form, and sustainability.
This thesis is organized into seven chapters. Chapter 1 introduces the research goals and questions, explaining the importance of the study. Chapter 2 describes how the new urban spatial dataset was created and provides an overview of the key data. Chapter 3 looks at how urban areas in the U.S. changed between 1900 and 1970, providing background for the main analyses. Chapter 4 studies how the Great Migration affected the size and shape of cities, while Chapter 5 examines the economic and environmental effects of these changes. Chapter 6 explains how changes in urban areas connected the Great Migration to economic and environmental outcomes. Finally, Chapter 7 brings the findings together, discusses what they mean for policy, highlights limitations, and suggests ideas for future research. These chapters work together to show how the Great Migration reshaped American cities and what that means for sustainability today.
Investigating the Dynamics of Meandering River Cutoffs: Relationships with Discharge, Land Cover and Spatial Clustering
(University of Waterloo, 2025-02-04) Sun, Letong
As climate change has become one of the major concerns across the globe, investigating the dynamics of meandering river evolution is substantial for urban river management and flood mitigation plans. In recent years, the study on river cutoff has been given lots of attention, as its occurrences and impacts were unpredictable and catastrophic. This study investigates its relationship with high-flow events, land cover and spatial clustering through flood frequency analysis, cutoff ratio criterion and spatial cluster analysis. 1,186 river cutoffs across the United States are located and identified based on Google Earth Imagery. 12 highly sinuous rivers with high cutoff occurrences are then selected and processed through R Studio and ArcGIS. The results show no strong correlation between high-flow events and cutoff occurrence across the study areas. Discharges with an average of approximately eleven-year return period are associated with cutoff occurrences. With the installation of the cutoff ratio in the dataset, it is found that chute cutoffs with higher CRm_m values are likely to occur on land cover types with lower erosion resistance. Neck cutoffs are usually found in floodplains less susceptible to erosion, particularly in undisturbed vegetated areas. Spatial cluster analysis shows that neck cutoffs are significantly clustered at all scales, whereas chute cutoffs exhibit relatively lower clustering tendencies and tend to be more event-driven. Minimizing the random disturbances in the analysis, this study collectively validates the non-random behaviour of cutoff occurrences, which further calls attention to the importance and viability of assessing and predicting cutoff evolution in urban planning and flood management.
Examining Computer-Generated Aeronautical English Accent Testing and Training
(University of Waterloo, 2025-02-04) Seong, Hyun Su
Objective: This thesis focused on the persisting problem of language-related issues, in pilot-air traffic controller (ATC) communication, particularly in relation to foreign accents interfering with pilots’ understanding. It examined the effect of foreign accents embedded in human and computer voice (HV, CV), as well as demographic background on the level of understanding of the participants.
Background: Studies focusing on the impacts of foreign accents in Aviation English (AE) are scant. Accents have been identified as one of the main contributors to miscommunication between pilot-ATC radiotelephony communication in the air, thereby endangering flight safety. It is necessary to examine how to train ab initio and returning pilots on extracting accurate meanings from an accented instruction coming from ATCs. This thesis introduces a Text-to-Speech (TTS) supported by artificial intelligence for such training.
Method: Multiple studies (a total of six) were conducted: 2 literature reviews, 4 empirical studies. For the empirical studies, 50 participants from the University of Waterloo who had experiences with flight or had experience in listening to pilot-ATC communications were recruited. They were put into two Voice Groups (HV and CV) one of which played only human voices and the other TTS. They completed two rounds (Round 1 and 2) of listening tests that contained both Aviation Script (AS; scripts read in foreign accents that were related to aviation context) and Neutral Scripts (NS; non-aviation scripts read in foreign accents with no contextual background). The foreign accents used in the listening tests along with native-accented English were three of the ICAO’s main languages: Arabic, Spanish, and French. Scores were analyzed according to the Script Types (NS, AS), Accents (Arabic, Spanish, French), Rounds (1 and 2), and Demographic Profiles (Age, Gender, Years of Speaking English, Flight Hours, Flight Ratings, Language Background, Familiarity with Arabic, Spanish, French, and Aviation English).
Results: For the empirical studies, in the HV group, participants improved their scores from round 1 to 2 in the AS portion of the tests. In the CV group, participants improved their scores in NS. Examination of demographic information showed that non-native English speakers (NNES) tended to perform more poorly on average than native English speakers (NES). Being familiar with Aviation English was beneficial for completing listening tests. Also, having a higher flight rating was beneficial. Having more years of speaking English was only partially advantageous. Post survey results were analyzed, and it was found that participants in the CV group found the speech mostly unnatural. Those in the HV group also expressed difficulty in understanding due to accents but mentioned that the speech was clear, and scripts were representative of real-life pilot-ATC communication. Participants expressed foreign accents interfered with their process of logical deduction when choosing answers on the tests. Participants – regardless of whether they belonged to the HV or CV group – found NS difficult and challenging due to lacking contexts when answering questions on the tests. For AS, participants were able to piece together information using contextual knowledge related to aviation.
Conclusion: Accents do interfere with pilots’ understanding in radiotelephony communication by making extracting content challenging, which in turn makes interpreting messages or instruction difficult. This is an important finding as it will affect situational awareness to a certain extent when making decisions on the fly. Pilots have to multi-task whenever possible to keep the passengers safe and to find the best route to get to a destination that maximizes fuel efficiency but minimizes passenger wait times. Communication plays a large role in deciding the fate of an aircraft’s journey. In this logic, accents can be said to be at the core of this overarching issue with language in the context of aviation. Therefore, training with a new technology such as TTS, along with other educational resources, could confer a valuable experience and exposure to pilots who are either beginning or re-starting their language training.