42 research outputs found
Optimal design of unmodeled linear systems using control-based continuation
No full textThis thesis describes the use of control-based continuation for design optimization, in the presence of constraints and without access to a model, of the response of a linear system to harmonic input. A proof of concept of this paradigm is presented in the context of an armature-controlled DC motor.
Specifically, three design problems are formulated with the objective function equal to the maximum angular velocity response to a harmonic torque disturbance, and a constraint that is imposed on each of three distinct stability margins, respectively. The analysis shows that the simulation model for the DC motor may be treated analogously to an actual experiment with all information drawn from real-time measurements, rather than from the model itself. The control-based continuation paradigm is formulated in terms of a non-invasive, yet locally stabilizing control scheme, which can be tuned to accelerate convergence to the steady state response. The numerical analysis uses the matlab-compatible continuation platform coco to determine the implicit relationship between model parameters that results from the constraint, and to evaluate the objective function along the corresponding constraint manifold. A comparison between a scheme that relies on finite differences for approximating the problem Jacobian and an algorithm based on the Broyden update is also included.Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-08-10 without embargo termsThe student, Tonghui Cui, accepted the attached license on 2017-04-25 at 13:41.The student, Tonghui Cui, submitted this Thesis for approval on 2017-04-25 at 13:53.This Thesis was approved for publication on 2017-04-26 at 08:36.DSpace SAF Submission Ingestion Package generated from Vireo submission #11045 on 2017-08-10 at 13:46:17Made available in DSpace on 2017-08-10T19:16:08Z (GMT). No. of bitstreams: 2
CUI-THESIS-2017.pdf: 734486 bytes, checksum: a7e9a2393d2409b10019cf3332808b0b (MD5)
LICENSE.txt: 4208 bytes, checksum: 502f9d84a0a8f948289e72c868b248c6 (MD5)
Previous issue date: 2017-04-2
Reliability-based co-design and its applications to wind energy and mobile energy storage systems
No full textAutonomous systems, such as autonomous driving vehicles, unmanned aerial vehicles (UAVs), and field robots, received much attentions recently. The performance of autonomous systems relies on both its physical design and the appropriate control strategies, which often takes place at an early stage of design. The plant design and the control design are strongly coupled. Neglecting this coupling effect may cause an imbalance in the feasible design spaces of plant design and control design, such as over-constrained operation conditions, over design, or requirement of skilled operators, which hinders the development of autonomous systems. On the other hand, the products are manufactured goods and usually operate in environments with uncertainty. Reliable operation of such systems ask for balanced physical design and feasible control decisions to address the parametric uncertainty and stochastic environmental disturbances.
While integrated physical and control system co-design has been demonstrated successfully on several engineering system design applications, it has been primarily applied in a deterministic manner without considering uncertainties. An opportunity exists to study non-deterministic co-design strategies, taking into account various uncertainties in an integrated co-design framework. While significant advancements have been made in co-design and RBDO separately, little is known about methods where reliability-based dynamic system design and control design optimization are considered jointly. In this research, we investigate optimal design and control of dynamical systems with model parametric uncertainties, which presumably operate in uncertain environments. Techniques in control co-design (CCD) and reliability-based design optimization (RBDO) are adapted and integrated to solve the proposed problem. Since the proposed method adopts the idea of multi-disciplinary design optimization, it can improve the performance of autonomous systems without leveraging the difficulty in design and control for systems with uncertainties.
First, the problem formulation and strategies to solve the reliability-based control co-design problem is presented. A comparison of accuracy and efficiency is made using numerical and simple engineering case studies. The method is then applied to a horizontal axis wind turbine. The uncertain wind load and model parameters of a wind turbine are compensated through active control or endured by a reliable design regarding its aerodynamics and structural dynamics. Different strategies of reliability assessment are also compared, which provides insights on their advantages and limits under different cases.
In the second application, reliability-based control co-design is applied to Lithium-ion battery. The electrode and charging current are optimized to minimize its charging time while regulating its aging effect for reasonable cycle life. The multi-scale nature of the problem requires first principle model to preserve the coupling effect between electrode design at the micro scale and the charging control at the macro scale. However, it is not feasible to use the first principle model for control optimization. A hybrid physics and machine learning strategy is proposed in this work, which extends the applicability of reliability-based control co-design to multi-scale problems.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01The student, Tonghui Cui, accepted the attached license on 2021-07-14 at 12:23.The student, Tonghui Cui, submitted this Dissertation for approval on 2021-07-14 at 12:46.This Dissertation was approved for publication on 2021-07-16 at 14:17.DSpace SAF Submission Ingestion Package generated from Vireo submission #16820 on 2022-01-12 at 13:04:15Made available in DSpace on 2022-01-12T22:55:01Z (GMT). No. of bitstreams: 2
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Previous issue date: 2021-07-16Embargo set by: Seth Robbins for item 121217
Lift date: 2024-01-12T22:55:09Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 121217
Lift date: 2024-01-12T22:56:20Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemAuthor requested closed access (OA after 2yrs) in Vireo ETD systemLimite
Multi-channel quasi-adaptive processing based on low and slow targets in complex environment
No full textSurrogate Model Assisted Lithium-Ion Battery Co-Design for Fast Charging and Cycle Life Performances
No full textA Comparative Study of Formulations and Algorithms for Reliability-Based Co-Design Problems
No full textFrom efficiency to resilience: unraveling the dynamic coupling of land use economic efficiency and urban ecological resilience in Yellow River Basin
No full textAbstract This study investigates the Dynamic Coupling between Land Use Economic Efficiency (LUEE) and Urban Ecological Resilience (UER) in the Yellow River Basin (YRB). This exploration is pivotal for elucidating the interaction mechanisms between economic growth and ecological governance. Furthermore, understanding this relationship is essential for fostering high-quality, sustainable urban development in the YRB. Utilizing panel data from 56 cities spanning 2003 to 2020, this study employed the coupling coordination degree (CCD) model, spatial correlation analysis, Kernel density estimation, convergence model, and Geodetector to systematically analyze the spatio-temporal distribution, dynamic trend, and determinants of the CCD between LUEE and UER in the YRB. The findings indicate that: (1) A general upward trend in both LUEE and UER, accompanied by a steady improvement in their CCD. (2) Significant spatial disparities in their CCD, with higher levels in the lower reaches. (3) Marked positive spatial autocorrelation, predominantly characterized by clusters where high (low) values are surrounded by high (low) values. (4) Regarding the impact of individual factors, government fiscal budget expenditure demonstrates the most robust explanatory power for the CCD within the YRB. Concerning the effects of two-factor interactions, the interplay between industrial structure upgrading and government fiscal budget expenditure emerges as the most significant determinant in influencing the CCD between LUEE and UER. This study enhances our comprehensive understanding of the interplay between economic and ecological systems. It offers scientific insights and strategic direction for harmonizing ecological governance with urban economic growth at both the regional and global scales
Significant role of ultramicropores on capacitive properties of polypyrrole-based carbons
No full textUnveiling the Spatio-Temporal Evolution and Key Drivers for Urban Green High-Quality Development: A Comparative Analysis of China’s Five Major Urban Agglomerations
No full textFaced with the dual challenges of ecological degradation and economic deceleration, promoting urban green high-quality development (UGHQD) is pivotal for achieving economic transformation, ecological restoration, and regional sustainable development. While the existing literature has delved into the theoretical dimensions of UGHQD, there remains a notable dearth of empirical studies that quantitatively assess its developmental levels, spatio-temporal evolution, and driving factors. This study examines 107 cities of China’s five major urban agglomerations from 2003 to 2020, constructing a comprehensive evaluation indicator system for UGHQD. By employing methodologies, including the Dagum Gini coefficient, Kernel density estimation, Markov chain, and geographical detector, this study extensively assesses the spatial difference, dynamic evolution, and underlying driving forces of UGHQD in these urban agglomerations. The findings indicate: (1) The UGHQD level of the five major urban agglomerations has witnessed a consistent year-over-year growth trend, with coastal agglomerations like the Pearl River Delta (PRD) and Yangtze River Delta (YRD) outperforming others. (2) Pronounced regional differences exist in UGHQD levels across the urban agglomerations, with inter-regional differences primarily contributing to these differences. (3) The dynamic evolution of UGHQD distribution generally transitions from a centralized to a decentralized pattern, with a marked “club convergence” characteristic hindering cross-type leaps. (4) While a range of factors drive UGHQD in these agglomerations, technological innovation stands out as the principal factor inducing spatial differentiation. The comprehensive analysis and findings presented in this research not only contribute to academic knowledge but also hold practical implications for policymakers and practitioners striving for environmentally conscious land use planning and urban management
From Imbalance to Synergy: The Coupling Coordination of Digital Inclusive Finance and Urban Ecological Resilience in the Yangtze River Economic Belt
No full textIn the context of rapid urbanization and digitalization, scientifically assessing the spatio-temporal interaction between digital inclusive finance (DIF) and urban ecological resilience (UER) is crucial for promoting the coordinated development of the regional ecology and economy. This study investigates the spatiotemporal evolution of the coupled coordination degree (CCD), the decoupling phenomenon, and its hindering factors in the Yangtze River Economic Belt (YREB) by utilizing the kernel density analysis, standard deviation ellipse, decoupling model, and obstacle degree analysis. Through systematic analyses, this paper aims to elucidate the development disparities among regions within the YREB, identify problematic areas, and propose targeted improvement measures. The results show that (1) The CCD between DIF and UER in the YREB has increased annually from 2011 to 2020. However, there are persistent imbalances, with an overall low level of coordination and uneven spatial development, and a trend of “higher coordination in the east and lower coordination in the west”. (2) The overall CCD of the YREB has reached at least the primary coordination level, with the coupling enhancement speed ranked as “downstream > midstream > upstream”, and regional differences decreasing. (3) The decoupling analysis reveals a predominant decoupling trend between DIF and UER, indicating that the digitization of financial services has not concurrently increased ecological pressures. (4) The obstacle degree analysis identifies resilience and digitalization as major barriers hindering CCD. This study provides a scientific basis and analytical framework for understanding the current spatiotemporal interaction between DIF and UER in the YREB, offering an important reference for formulating more effective policies
