Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 16 of 16 for “"Learning-based control"”.
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Learning-based control of a cyberoctopus
… of octopuses, my work focuses on designing control strategies for a simulated soft-bodied octopus-like robot, the CyberOctopus. The continuous deformation and intricate mechanics of soft arms pose challenges in developing dynamic control models, especially when engaging with moving objects …
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Learning-based control system design: theory and applications
Reinforcement learning (RL) offers a versatile, data-driven framework for feedback controller synthesis applicable to a wide range of dynamical systems. Its adaptability makes RL suitable for large-scale, complex control applications where environments change rapidly and precise symbolic modeling …
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Learning-Based Control for Optically Trapped Non-Spherical Particles
… has enabled the application of modern, model-based control methods to the trapping of spherical particles resulting in significant improvements in experimental outcomes. The trapping of non-spherical particles, for example rod-shaped bacteria or engineered microstructures, is also an important …
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Reinforcement learning based control for arrays of point absorber wave energy converters
… is poor. Performance can be improved using a control system to select different values of damping acting on the point absorber through the PTO. The selection of values can be achieved using reinforcement learning algorithms, such as Q-learning. Performance of the control system was evaluated …
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Deep Reinforcement Learning-based Control Strategies for Enhancing Energy Management in HVAC Systems
L'abstract è presente nell'allegato / the abstract is in the attachment
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Towards Machine Learning-Based Control of Autonomous Vehicles in Solar Panel Cleaning Systems
<p>This thesis presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in …
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Safe and adaptive reinforcement learning for robotics applications
In recent years, learning-based control methods, especially those leveraging the power of reinforcement learning (RL) and deep learning, have demonstrated impressive performance in complex robotics control tasks. However, they often suffer from the lack of safety and robustness guarantees, which …
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Fault Tolerant Deep Reinforcement Learning for Aerospace Applications
… algorithms that not only stabilize or control the system, but rather would also include various factors such as optimality, robustness, adaptability, tracking, decision making, and many more. In this thesis, a deep-learning-based control system is designed with fault-tolerant and …
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INTELLIGENT DYNAMIC THERMAL CONTROL USING DEEP LEARNING AND REINFORCEMENT LEARNING
… practical and intelligent dynamic thermal control (DTC) methods for data centers (DCs) using deep learning and reinforcement learning (RL). The research investigates existing RL algorithms for DTC and proposes a comprehensive analysis framework considering the algorithm, control objective, …
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Control of Grid-Connected Converters using Deep Learning
With the rise of inverter-based resources (IBRs) within the power system, the control of grid-connected converters (GCC) has become pertinent due to the fact they interface IBRs to the grid. The conventional method of control for grid-connected converters (GCCs) such as the voltage-sourced …
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Scalable Assembly of General Objects
… global multi-step planning with local reactive learning-based control to enable generalizable and precise assembly. Such an integrated paradigm effectively leverages the best of both worlds, accomplishing results that neither planning nor learning could achieve alone. For planning, I leverage …
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Advancing Kinematic Control from Rigid Robots to Dynamic Bio-Inspired Systems for Adaptive Behaviours
… bio-inspired systems are far more difficult to control due to complex kinematics and dynamics. While various control strategies exist, closed-loop kinematic control offers the advantage of implicitly managing quasi-static dynamic internal and external forces. This thesis presents a conceptual …
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Actuator Optimization and Control of Pediatric Knee Exoskeleton for Community-based Mobility Assistance: More Lightweight, More Affordable, and More Stable
… pediatric exoskeletons are typically clinic-based since they are either tethered or portable but cumbersome, and their design is often not optimized across a range of environments and users. Child growth progressively alters key exoskeleton design requirements, yet no prior work investigated …
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Suspension Controls and Parameter Estimation Using Accelerometer Based Intelligent Tires
… estimating vital vehicle states and developing control algorithms for automotive suspensions and vehicle stability. A parametric model of an automotive monotube damper is developed and several control algorithms for semi-active suspensions have been developed. An extensive comparison of …
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Stochastic Optimization For Multi-Agent Statistical Learning And Control
… accurate, and affordable complexity statistical learning among networks of autonomous agents. We begin by noting the connection between statistical inference and stochastic programming, and consider extensions of this setup to settings in which a network of agents each observes a local data …
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Modelling and optimal control of wave energy systems: A data-driven approach
L'abstract è presente nell'allegato / the abstract is in the attachment