Browsing by Author "Debiasi, M."
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Item Open Access Control of subsonic cavity flows by neural networks-analytical models and experimental validation(American Institute of Aeronautics and Astronautics, 2005) Efe, M. Ö.; Debiasi, M.; Yan, P.; Özbay, Hitay; Samimy, M.Flow control is attracting an increasing attention of researchers from a wide spectrum of specialties because of its interdisciplinary nature and the associated challenges. One of the main goals of The Collaborative Center of Control Science at The Ohio State University is to bring together researchers from different disciplines to advance the science and technology of flow control. This paper approaches the control of subsonic cavity flow, a study case we have selected, from a computational intelligence point of view, and offers a solution that displays an interconnected neural architecture. The structures of identification and control, together with the experimental implementation are discussed. The model and the controller have very simple structural configurations indicating that a significant saving on computation is possible. Experimental testing of a neural emulator and of a directly-synthesized neurocontroller indicates that the emulator can accurately reproduce a reference signal measured in the cavity floor under different operating conditions. Based on preliminary results, the neurocontroller appears to be marginally effective and produces spectral peak reductions analogous to those previously observed by the authors using linearcontrol techniques. The current research will continue to improve the capability of the neural emulator and of the neurocontroller.Item Open Access Experimental results and bifurcation analysis on scaled feedback control for subsonic cavity flows(IEEE, 2006) Yuan, X.; Caraballo, E.; Debiasi, M.; Little, J.; Serrani, A.; Özbay, Hitay; Samimy, M.In this paper, we present the latest results of our ongoing research activities in the development of reduced-order models based feedback control of subsonic cavity flows. The model was developed using the Proper Orthogonal Decomposition of Particle Image Velocimetry images in conjunction with the Galerkin projection of the Navier-Stokes equations onto the resulting spatial eigenfunctions. Stochastic Estimation method was used to obtain the state estimation of the Galerkin system from real time surface pressure measurements. A linear-quadratic optimal controller was designed to reduce cavity flow resonance and tested in the experiments. Real-time implementation shows a significant reduction of the sound pressure level within the cavity, with a remarkable attenuation of the resonant tone and a redistribution of the energy into various modes with lower energy levels. A mathematical analysis of the performance of the LQ control, in agreement with the experimental results, is presented and discussed.Item Open Access Experimental study of linear closed-loop control of subsonic cavity flow(2006) Yan P.; Debiasi, M.; Yuan X.; Little J.; Özbay, Hitay; Samimy, M.A study is presented of the modeling and implementation of different concepts for linear feedback control of a single-mode resonance shallow cavity flow. When a physics-based linear model is used for cavity pressure oscillations-, an H∞ controller was designed and tested experimentally. It significantly reduced the main Rossiter mode for which it was designed, while leading to strong oscillations at other Rossiter modes. Other linear control methods such as Smith predictor controller and proportional integral derivative (PID) controller exhibited similar results. The ineffectiveness of using fixed linear models in the design of controllers for the cavity flows is discussed. A modification of the PID design produced a parallel-proportional with time-delay controller that remedied this problem by placing zeros at the frequencies corresponding to other resonance states. Interestingly, it was observed that introducing the same zero to the H∞ controller can also successfully avoid the strong oscillations at other Rossiter modes otherwise observed in the single-mode-based design. The parallel-proportional with time-delay controller was compared to a very effective open-loop method for reducing cavity resonance and exhibited superior robustness with respect to departure of the Mach number from the design conditions. An interpretation is presented for the physical mechanisms by which the open-loop forcing and the parallel-proportional with time-delay controllers reduce the cavity flow noise. The results support the idea that both controls induce in the system a rapid switching between modes competing for the available energy that can be extracted from the mean flow.Item Open Access Feedback control design for subsonic cavity flows(2009) Yuan X.; Caraballo, E.; Little J.; Debiasi, M.; Serrani, A.; Özbay, Hitay; Myatt J.H.; Samimy, M.A benchmark problem in active aerodynamic flow control, suppression of strong pressure oscillations induced by flow over a shallow cavity, is addressed in this paper. Proper orthogonal decomposition and Galerkin projection techniques are used to obtain a reduced-order model of the flow dynamics from experimental data. The model is made amenable to control design by means of a control separation technique, which makes the control input appear explicitly in the equations. A prediction model based on quadratic stochastic estimation correlates flow field data with surface pressure measurements, so that the latter can be used to reconstruct the state of the model in real time. The focus of this paper is on the controller design and implementation. A linear-quadratic optimal controller is designed on the basis of the reduced-order model to suppress the cavity flow resonance. To account for the limitation on the magnitude of the control signal imposed by the actuator, the control action is modified by a scaling factor, which plays the role of a bifurcation parameter for the closed-loop system. Experimental results, in qualitative agreement with the theoretical analysis, show that the controller achieves a significant attenuation of the resonant tone with a redistribution of the energy into other frequencies, and exhibits a certain degree of robustness when operating in off-design conditions.Item Open Access Modeling and feedback control for subsonic cavity flows: a collaborative approach(IEEE, 2005) Yan, P.; Debiasi, M.; Yuan, X.; Caraballo, E.; Serrani, A.; Özbay, Hitay; Myatt, J. M.; Samimy, M.Feedback control of aerodynamic flows is attracting the attention of researchers from a wide spectrum of specialties, because of its interdisciplinary nature and the challenges inherent to the problem. One of the main goals of the Collaborative Center of Control Science at The Ohio State University is to bring together researchers from different disciplines to advance the science and technology of flow control. This paper presents a comprehensive summary of the effort of the Center on modeling and feedback control of subsonic cavity-flow resonance. In particular, we give a detailed description of the experimental apparatus, including the wind tunnel testbed, the data measurement and acquisition system, and the real time control system. Reduced-order models of the flow dynamics based on physically-oriented linear models and Proper Orthogonal Decomposition are introduced and their effectiveness for control system design discussed. Finally, results obtained with experimental and model-based controller design are discussed.Item Open Access Modeling of subsonic cavity flows by neural networks(IEEE, 2004-06) Efe, M.Ö.; Debiasi, M.; Özbay, Hitay; Samimy, M.Influencing the behavior of a flow field is a core issue as its improvement can yield significant increase of the efficiency and performance of fluidic systems. On the other hand, the tools of classical control systems theory are not directly applicable to processes displaying spatial continuity as in fluid flows. The cavity flow is a good example of this and a recent research focus in aerospace science is its modeling and control. The objective is to develop a finite dimensional representative model for the system with appropriately defined inputs and outputs. Towards the goal of reconstructing the pressure fluctuations measured at the cavity floor, this paper demonstrates that given some history of inputs and outputs, a neural network based feedforward model can be developed such that the response of the neural network matches the measured response. The advantages of using such a model are the representational simplicity of the model, structural flexibility to enable controller design and the ability to store information in an interconnected structure.Item Open Access Neural network-based modelling of subsonic cavity flows(Taylor & Francis, 2008) Efe, M. Ö.; Debiasi, M.; Yan, P.; Özbay, Hitay; Samimy, M.A fundamental problem in the applications involved with aerodynamic flows is the difficulty in finding a suitable dynamical model containing the most significant information pertaining to the physical system. Especially in the design of feedback control systems, a representative model is a necessary tool constraining the applicable forms of control laws. This article addresses the modelling problem by the use of feedforward neural networks (NNs). Shallow cavity flows at different Mach numbers are considered, and a single NN admitting the Mach number as one of the external inputs is demonstrated to be capable of predicting the floor pressures. Simulations and real time experiments have been presented to support the learning and generalization claims introduced by NN-based models.Item Open Access Seven tuning schemes for an ADALINE model to predict floor pressures in a subsonic cavity flow(Sage Publications Ltd., 2009) Efe, M. Ö.; Debiasi, M.; Yan, P.; Özbay, Hitay; Samimy, M.This paper presents a simple yet effective one-step-ahead predictor based on an adaptive linear element (ADALINE). Several tuning schemes are studied to see whether the obtained model is consistent. The process under investigation is a subsonic cavity flow system. The experimental data obtained from the system is post-processed to obtain a useful predictor. The contribution of the paper is to demonstrate that despite the spectral richness of the observed data, a simple model with various tuning schemes can help to a satisfactory extent. Seven algorithms are studied, including the least mean squares (LMS), recursive least squares (RLS), modified Kaczmarz's algorithm (MK), stochastic approximation algorithm (SA), gradient descent (GD), Levenbergĝ€ "Marquardt optimization technique (LM) and sliding mode-based tuning (SM). The model and its properties are discussed comparatively.Item Open Access Support vector networks for prediction of floor pressures in shallow cavity flows(IEEE, 2007) Efe, M. Ö.; Debiasi, M.; Yan, P.; Özbay, Hitay; Samimy, M.During the last decade, Support Vector Machines (SVM) have proved to be very successful tools for classification and regression problems. The representational performance of this type of networks is studied on a cavity flow facility developed to investigate the characteristics of aerodynamic flows at various Mach numbers. Several test conditions have been experimented to collect a set of data, which is in the form of pressure readings from particular points in the test section. The goal is to develop a SVM based model that emulates the one step ahead behavior of the flow measurement at the cavity floor. The SVM based model is built for a very limited amount of training data and the model is tested for an extended set of test conditions. A relative error is defined to measure the reconstruction performance, and the peak value of the FFT magnitude of the error is measured. The results indicate that the SVM based model is capable of matching the experimental data satisfactorily over the conditions that are close to the training data collection conditions, and the performance degrades as the Mach number gets away from the conditions considered during training.