학위논문 (박사)-- 서울대학교 대학원 : 기계항공공학부, 2013. 8. 김현진. ; 본 박사학위 논문에서는 박리 유동 제어에 대한 비모델 기반의 적응 역변환 제어기와 proper orthogonal decomposition을 이용한 유동 모델링 및 변형된 이차 확률 추정 기법과 통합된 모델 기반의 유동 제어기를 제안하였다. 또한 본 논문에서는 제안된 박리 유동의 제어 기법을 검증하기 위하여 풍동 실험을 수행하였으며, 실시간 측정을 위하여 MEMS 압력 센서 및 Synthetic jet 구동기를 사용하였다. 비모델 기반의 제안된 기법의 경우, 본래의 비선형 특성을 갖는 박리 유동에 대한 적응 필터링 기법을 이용한 정밀한 실시한 변환 유동 모델을 구성하고 반복 신경회로망 기법을 이용한 적응 앞먹임 제어 기법을 이용하고 모델 자유 기법의 일종인 극값 추종 기법과 통합하는 것을 제안하였다. 제안된 비모델 기반의 기법을 이용하여 박리 유동의 상태를 정밀하게 제어가는 것을 실험적으로 검증하였다. 모델 기반의 제안된 기법의 경우, 널리 알려진 축소 유동 모델은 복잡하고 계산적인 측면에서 비효율적이다. 제안된 proper orthogonal decomposition을 이용한 유동 모델링을 효율적으로 수행하였고 이를 수치적, 실험적으로 검증하였다. 제안된 유동 모델링을 바탕으로 PIV와 같은 고가의 장비 없이도 실시간 유동의 상태를 추정할 수 있는 장점을 가진다. 또한, 제안된 유동 모델링을 바탕으로 효과적인 유동 제어기를 설계하고 실험적으로 검증을 하였다. 제안된 비모델 기반의 유동 제어 기법을 통해 박리 유동의 효과적인 제어를 수행하였으며, 그에 따라 향상된 유동 상태를 얻을 수 있다. 또한, 이는 에너지 효율의 측면에서 매우 효과적인 연구로 향후 박리 유동 제어 연구 분야에서의 다양하게 적용 및 응용이 가능할 것으로 기대된다. ; This dissertation involves an active flow control system for the separated flow over an airfoil (NACA 64A210) and wing of the unmanned combat aerial vehicle (UCAV) model in a subsonic wind tunnel. An active flow control system is mainly composed of the piezoelectrically driven synthetic jet actuator, pressure sensors and closed-loop controllers including model-free and model-based controller. The objective of this dissertation is to develop two effective closed-loop control strategies for the flow separation problem. Before performing the closed-loop experiments, the effectiveness of the jet actuation is first investigated by open-loop tests in various operating conditions to investigate the suitable control variable. The pressure gradient, which is calculated from the difference of mean pressure coefficients between two sensor positions, is a criterion of flow reattachment and pressure recovery. Therefore, the pressure gradient is selected as control parameter to be controlled for separated flow. As the first approach, the model-free adaptive controller is developed for controlling the separated flow. The degree of the separated flow which can be expressed as the pressure gradient must effectively and efficiently be controlled by using the adaptive inverse control and extremum seeking control schemes. In the model-free adaptive approach, the adaptive inverse controller and extremum seeking controller are used to obtain the actuation frequency and magnitude of the piezoelectric driven actuators, respectively. Simulation and experimental results based on the model-free adaptive control system demonstrate the satisfactory tracking performance for the pressure recovery. The turbulent kinetic energy (TKE) can be regarded as the kinetic energy of the dynamic portion of the turbulent fluid flow and estimated by the proper orthogonal decomposition and the modified stochastic estimation method. Using TKE as an alternative control parameter, the feasibility in terms of the tracking performance of TKE is investigated using the proposed model-free adaptive controller in combination with a modified stochastic estimation method that estimates the TKE. Second, for the model-based strategy, this dissertation presents a new reduced order model that consists of ideas from subspace identification, modified stochastic estimation and Proper Orthogonal Decmposition (POD) methods. The subspace identification model is developed based on the computational fluid dynamics results of the separated flow. The POD and modified quadratic stochastic estimation methods which describe the fluctuating characteristics of the flow are used in combination with the linear model obtained from the subspace identification method. The proposed reduced order model is validated by simulation and experimental results. Based on the proposed reduced order model, the model-based controller is successfully evaluated delaying the flow separation in the experimental setup involving the NACA 64A210 airfoil, synthetic jet actuators and pressure sensors. ; Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.1 Model-Free Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2.2 Model-Based Control . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 Objectives and Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.4 Thesis Orgarnization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2 Experimental Setup and Baseline Analysis . . . . . . . . . . . . . . . . . . . . . 11 2.1 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2 Open-Loop Experimental Results and Analysis . . . . . . . . . . . . . . . 18 2.2.1 Baseline Analysis for Closed-Loop Control . . . . . . . . . . . . . . 18 2.2.2 Open-Loop Experimental Results of an NACA 64A210 Airfoil . . . 20 2.2.3 Open-Loop Experimental Results of an UCAV Model . . . . . . . . 40 3 Model-Free Adaptive Control for Separated Flow . . . . . . . . . . . . . . . . . 52 3.1 Closed-Loop Feedback Control Strategies . . . . . . . . . . . . . . . . . . . 52 3.1.1 Closed-Loop Feedback Control System Using a PID Control Scheme 53 3.1.2 Closed-Loop Feedback Control System Using an Adaptive Control Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.3 Adaptive Plant Identification . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Adaptive Feedforward Control . . . . . . . . . . . . . . . . . . . . . 59 3.1.5 Adaptive Inverse Control Combined With an Extremum-Seeking Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.2.1 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.2.2 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4 Model-Free Adaptive Control with Proper Orthogonal Decomposition and Modified Stochastic Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 4.1 Flow Field Estimation Technique . . . . . . . . . . . . . . . . . . . . . . . 77 4.1.1 Classical Proper Orthogonal Decomposition . . . . . . . . . . . . . 78 4.1.2 Modified Stochastic Estimation . . . . . . . . . . . . . . . . . . . . 81 4.1.3 The Model-Free Adaptive Control with POD and MLSE . . . . . . 82 4.1.4 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5 Model-Based Control Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.1 Reduced-Order Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.1.1 Projection Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.1.2 Reduced-Order Model . . . . . . . . . . . . . . . . . . . . . . . . . 95 5.1.3 Quadratic Stochastic Estimation Modification of Flow Fields . . . . 105 5.2 Design of the Model-Based Controller . . . . . . . . . . . . . . . . . . . . . 108 5.3 Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 6.1 Summary of the Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 6.2 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 ; Doctor
Effective Model-Free and Model-Based Strategies for Closed-Loop Flow Separation Control ; 폐루프 박리 유동 제어를 위한 효과적인 비모델 및 모델 기반의 제어기법
2013-01-01
Theses
Electronic Resource
English
DDC: | 629 |
Exploring Strategies for Closed-Loop Cavity Flow Control
AIAA | 2004
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Emerald Group Publishing | 2018
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