Model-based controller design and simulation of a marine chiller
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For the past decade, the US Navy has committed to fundamental research and technology development on its next generation of surface ships. The vision is that these warships will be dynamically reconfigurable, energy-efficient, and have state-of-the-art pulsed energy weapons and sensors onboard. These developments represent a significant increase in highly dynamic on-board electrical systems that will produce correspondingly large amounts of dynamic heat generation, which, if not managed properly, will likely produce significant thermal side effects. In previous work, a highly customizable simulation framework has been developed to address thermal management issues across both the mechanical and electrical domains. This software environment is called the Dynamic Thermal Modeling and Simulation (DTMS) framework. The purpose of the current work is to introduce modern control theory into DTMS, thus providing the framework with the ability to control large-scale system simulations. The research reported in this thesis uses control of a marine chiller as a simulation vehicle. Several control strategies were implemented. These included the well-established PID controller as well as a new controller based on optimal control theory. Results for chiller simulations in the case of no-control, PID control, and optimal control are presented here. The comparative effectiveness of these controls in bringing the chiller to startup equilibrium is investigated. Response of the chiller model and the optimal controller to highly dynamic, varying heat loads was tested. The PID controller in DTMS is modeled as a special case of the transfer function control scheme. A PID controller is simple to implement but responses are inherently local and multiple controls in a system or subsystem simulation can easily lead to conflicts. The optimal control problem has been modeled as an Infinite Horizon Linear Quadratic Regulator (LQR) problem. This formulation is not local and does not create undesirable effects in parts of the system that not controlled directly by controller inputs. Using the York 200-ton marine chiller as an example, specific steps required to formulate the LQR problem are documented in this report. Implementation of the LQR controller was demonstrated for the startup to steady-state function of the chiller at full load. Treatment of the optimal controller ends with simulation of the chiller and its LQR controller under the influence of varying dynamic heat loads in a chilled water loop. The heat load variation examined has highly transient characteristics that affect the temperature of the fresh water entering the chiller, as well as the refrigerant pressure and temperature in the evaporator. The LQR formulation is shown to actively adjust to these varying operating points in a smooth and responsive manner.