Improving the Accuracy and Scope of Control-Oriented Vapor Compression Cycle System Models

The benefits of applying advanced control techniques to vapor compression cycle systems are well know. The main advantages are improved performance and efficiency, the achievement of which brings both economic and environmental gains. One of the most significant hurdles to the practical application of advanced control techniques is the development of a dynamic system level model that is both accurate and mathematically tractable. Previous efforts in control-oriented modeling have produced a class of heat exchanger models known as moving-boundary models. When combined with mass flow device models, these moving-boundary models provide an excellent framework for both dynamic analysis and control design. This thesis contains the results of research carried out to increase both the accuracy and scope of these system level models. The improvements to the existing vapor compression cycle models are carried out through the application of various modeling techniques, some static and some dynamic, some data-based and some physics-based. Semiempirical static modeling techniques are used to increase the accuracy of both heat exchangers and mass flow devices over a wide range of operating conditions. Dynamic modeling techniques are used both to derive new component models that are essential to the simulation of very common vapor compression cycle systems and to improve the accuracy of the existing compressor model. A new heat exchanger model that accounts for the effects of moisture in the air is presented. All of these model improvements and additions are unified to create a simple but accurate system level model with a wide range of application. Extensive model validation results are presented, providing both qualitative and quantitative evaluation of the new models and model improvements.Air Conditioning and Refrigeration Project 17

Design of a Linear Time-Varying Cross-Coupled Iterative Learning Controller

In many manufacturing applications contour tracking is more important than individual axis tracking. Many control techniques, including iterative learning control (ILC), target individual axis error. Because individual axis error only indirectly relates to contour error, these approaches may not be very effective for contouring applications. Cross-coupled ILC (CCILC) is a variation on traditional ILC that targets the contour tracking directly. In contour trajectories with rapid changes, high frequency control is necessary in order to meet tracking requirements. This paper presents an improved CCILC that uses a linear time-varying (LTV) filter to provide high frequency control for short durations. The improved CCILC is designed for raster-scan tracking on a Cartesian robotic test platform. Analysis and experimental results are presented

A Learning Based Precool Algorithm for Utilization of Foodstuff as Thermal Energy Storage

Abstract — Maintaining foodstuff within predefined temper-ature thresholds is important due to legislative requirements and to sustain high foodstuff quality. This is achieved using a refrigeration system. However, these systems might not be dimensioned for hot summer days or possible component per-formance degradation. A learning based algorithm is proposed in this paper, which precools the foodstuff in an anticipatory manner based on the saturation level in the system on recent days. The method is evaluated using a simulation model of a supermarket refrigeration system and simulations show that thermal energy can be stored in foodstuff to cope with saturation in refrigeration equipment. Additional hardware or a system model is not required, making it easy to implement the method in existing systems. I

High Bandwidth Control of Precision Motion Instrumentation

This article presents a high-bandwidth control design suitable for precision motion instrumentation. Iterative learning control (ILC), a feedforward technique that uses previous iterations of the desired trajectory, is used to leverage the repetition that occurs in many tasks, such as raster scanning in microscopy. Two ILC designs are presented. The first design uses the motion system dynamic model to maximize bandwidth. The second design uses a time-varying bandwidth that is particularly useful for nonsmooth trajectories such as raster scanning. Both designs are applied to a multiaxis piezoelectric-actuated flexure system and evaluated on a nonsmooth trajectory. The ILC designs demonstrate significant bandwidth and precision improvements over the feedback controller, and the ability to achieve precision motion control at frequencies higher than multiple system resonances

A comparison of wave mode identification techniques

The four point measurements available from the Cluster mission enable spatiotemporal effects in data sets to be resolved. One application of these multipoint measurements is the determination of the wave vectors and hence the identification of wave modes that exist within the plasma. Prior to multi-satellite missions, wave identification techniques were based upon the interpretation of observational data using theoretically defined relations. However, such techniques are limited by the quality of the data and the type of plasma model employed. With multipoint measurements, wave modes can be identified and their wave directions determined purely from the available observations. This paper takes two such methods, a phase differencing technique and k-filtering and compares their results. It is shown that both methods can resolve the k vector for the dominant mirror mode present in the data. The phase differencing method shows that the nature of the wave environment is constantly changing and as such both methods result in an average picture of the wave environment in the period analysed. The k-filtering method is able to identify other modes that are present