가변속 냉동시스템의 강인제어를 위한 최적 슬라이딩 모드 제어기 설계

Abstract

Variable Speed Refrigeration System(VSRS) is called VSD(Variable Speed Drive) or VRF(Variable Refrigerant Flow) system. However, in the process of responding to change the cooling load, a sudden change in the mass flow rate of the refrigerant is accompanied due to the control of variable speed compressor. At this time, COP(Coefficient Of Performance) decreases due to changes in superheat and various side effects such as ‘liquid back phenomenon’ may occur. So the opening angle of the electronic expansion valve(EEV) must also be adjusted to prevent this phenomenon and keep maximum COP of the system. The control of the VSRS is composed of a multi-input multi-output(MIMO) that simultaneously controls the target temperature and superheat. Many control methods for the oil cooler system based on the VSRS have been suggested recently. Depending on whether the control target is modeled or not, it is mainly divided into a hard control and a soft control. Among the typical control methods of the VSRS, examples of the hard control method include PID control, optimal control(LQR, LQG), H-Infinity control, and Sliding Mode Control(SMC). The soft control method includes an example of Fuzzy Logic Control(FLC), one of the AI(Artificial Intelligence) techniques. In case of SMC, one of the robust control methods, is known to have a robust control performance for systems with uncertainty of model and disturbance. Also, the design of the controller is easier than H-infinity control and mu-synthesis control, which are known as a robust control method. Since the control logic can be intuitively understood, it has attracted attention as a robust control method recently. However, since the SMC is based on modern control theory, a state space model of the control target is required. In addition, when designing the controller, the SMC design parameters are selected by a trial and error method, and the chattering problem and steady state error occurring in the controlled variables remain a problem to be solved. As for the VSRS modeling method of the hard controller design, an analytic state space modeling method applying the Moving Boundary Model(MBM), which is one of the numerical methods of thermal-fluid systems, and the dynamic transfer function modeling method through an experiment near the operating point are proposed. State space model of applying the MBM method is expressed as a complex, high order nonlinear partial differential equation, it is not only impractical for controller design but also the uncertainty of the model is very large. Therefore, intuitive analysis and maintenance are very difficult. In addition, since the state space model based control requires feedback of state variables, state observer must be designed. It is difficult to understand the physical meaning of the state variables of the high-order model, and it is not easy to verify the validity of the designed observer. The experimental-based dynamic transfer function is easy to get a model of control target. However, it is obtained under a specific thermal environment and operating point, when the experimental conditions or the operating environment are different, the characteristic parameters of the nominal transfer function model change by tens of percent. In case of model-based control, since the parameters of the controller are related to the parameters of the model, it is difficult to secure the robust control performance when the model uncertainty is large, such as VSRS. Therefore, this paper use experimental-based dynamic transfer function model that is obtained near the operating point in order to solve the problem of impractical modeling point of view. It is a relatively simple experiment to obtain a transfer function model, so modeling is very simple compared to the MBM. In addition, this transfer function model is easy to intuitively understand the behavior of the control target through characteristic parameters. Based on this practical transfer function modeling method, a state space model is constructed to design a SMC and robust control performance is secured against model uncertainty and disturbances occurring in the VSRS. Especially, in this paper, by designing the SMC to have an optimal sliding surface, it was considered to have both robustness and optimality. Finally, the validity of the designed controller is verified through Matlab simulation and actual experiment for the oil cooler composed of VSRS. In addition, the effectiveness of SMC is verified by comparing the control performance with the PI controller.