Browsing by Author "Koeln, Justin P."
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Item Design and Validation of Switched Moving Boundary Modeling for Phase Change Thermal Energy Storage Systems(May 2023) Sakakini, Trent Joseph 2000-; Koeln, Justin P.; Ruths, Justin; Li, YaoyuThermal Energy Storage (TES) devices, which leverage the constant-temperature thermal capacity of the latent heat of a Phase Change Material (PCM), provide benefits to a variety of thermal management systems by decoupling the absorption and rejection of thermal energy. Control-oriented models are needed to predict the behavior of the TES to maximize the capabilities and efficiency of the overall system and experimental validation is needed to demonstration the validity of the simplifying assumptions used to produce these control- oriented models. This thesis experimentally demonstrates the predictive capabilities of a switched Moving Boundary (MB) model that captures the key dynamics of the TES with significantly fewer states as compared to traditional approaches. A graph-based modeling approach is used to model the heat flow through the TES and the moving boundary captures the time-varying liquid and solid regions of the TES. A Finite State Machine (FSM) is used to switch between four different modes of operation based on the State-of-Charge (SOC) of the TES. The switched MB approach is shown to have similar accuracy and lower computational cost compared to traditional modeling approaches when predicting the SOC of an experimental TES device.Item Robust Hierarchical Model Predictive Control of Graph-Based Power Flow Systems(Elsevier Ltd) Koeln, Justin P.; Alleyne, A. G.; Koeln, Justin P.A robust hierarchical model predictive control framework is presented for controlling a linear system of dynamically coupled subsystems. A graph-based modeling framework captures the conservation laws of power flow systems, for which control optimizes the storage and routing of energy to maximize transient and steady-state power throughput. A constructive approach is presented for developing an N-level hierarchical controller, which guarantees satisfaction of state and input constraints in the presence of signal and model uncertainty.Item Two-Level Hierarchical Mission-Based Model Predictive Control(Institute of Electrical and Electronics Engineers Inc.) Koeln, Justin P.; Alleyne, A. G.; Koeln, Justin P.A two-level hierarchical model predictive control (MPC) formulation is presented for constrained linear systems operating over a mission. Mission-based MPC is applicable to many control applications where the system operates for a finite time and stability about an equilibrium is not the primary objective. Instead, the primary control objective is to guarantee constraint satisfaction during operation as well as terminal constraints imposed on the final state of the system at the end of the mission. The secondary control objective is reference tracking, where references determine the desired operation for the system. A hierarchical control formulation permits the upper level controller to plan state trajectories over the entire mission, while a lower level controller modifies these trajectories to improve reference tracking. This decomposition of the control problem reduces computational cost, enabling real-time implementation for large systems with long missions. Feasibility proofs guarantee the constraint satisfaction while a numerical example demonstrates the efficacy of the approach.