Jian Sun

Bio: Jian Sun is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Aeroelasticity & Nonlinear system. The author has an hindex of 3, co-authored 6 publications receiving 72 citations.

Adaptive Reduced-Order-Model-Based Control-Law Design for Active Flutter Suppression

Abstract: The design of classic active flutter controllers has often been based on low-fidelity and low-accuracy linear aerodynamic models. Most of these models were usually treated as a linear time-invariant system, without considering time-varying parameters, such as the Mach number, the angle of attack, the Reynolds numbers, etc. A high-fidelity reduced-order model based on the proper orthogonal decomposition adaptation algorithm is used to develop a new general linear parameter-varying aeroservoelastic model with aerodynamic nonlinearity. A robust gain-scheduling control-law design method for active flutter suppression based on the proposed linear parametervarying model is investigated. The proposed design method is demonstrated with the Goland wing aeroelastic model. The simulation results show that the linear parameter-varying gain-scheduled controller can effectively suppress flutter over a range of airspeeds, and the flutter boundary in the transonic regime is simultaneously increased by nearly 20% to 30%.

Support-Vector-Machine-Based Reduced-Order Model for Limit Cycle Oscillation Prediction of Nonlinear Aeroelastic System

Abstract: It is not easy for the system identification-based reduced-order model (ROM) and even eigenmode based reduced-order model to predict the limit cycle oscillation generated by the nonlinear unsteady aerodynamics. Most of these traditional ROMs are sensitive to the flow parameter variation. In order to deal with this problem, a support vector machine- (SVM-) based ROM was investigated and the general construction framework was proposed. The two-DOF aeroelastic system for the NACA 64A010 airfoil in transonic flow was then demonstrated for the new SVM-based ROM. The simulation results show that the new ROM can capture the LCO behavior of the nonlinear aeroelastic system with good accuracy and high efficiency. The robustness and computational efficiency of the SVM-based ROM would provide a promising tool for real-time flight simulation including nonlinear aeroelastic effects.

Limit Cycle Oscillation Control for Transonic Aeroelastic Systems Based on Support Vector Machine Reduced Order Model

Abstract: Due to the difficulty in accurately predicting the limit cycle oscillation (LCO) generated by nonlinear unsteady aerodynamics in the transonic regime, neither the traditional system identification nor eigenmode-based reduced order model (ROM) are suitable for designing active LCO control law. A support vector machine (SVM) based ROM is investigated and an active control law design method based on the new ROM is proposed. A three-degree-of-freedom pitch and plunge aeroelastic systems in transonic flow is successfully demonstrated for the SVM-based ROM. The simulation results indicate that the active LCO control law can be designed and evaluated with good accuracy and efficiency by the SVM itself, without requiring intensive simulations of the CFD/CSD couple solver.

An Improved 3D Shape Recognition Method Based on Panoramic View

Abstract: Recognition of three-dimensional (3D) shape is a remarkable subject in computer vision systems, because of the lack of excellent shape representations. With the development of 2.5D depth sensors, shape recognition is becoming more important in practical applications. Many methods have been proposed to preprocess 3D shapes, in order to get available input data. A common approach employs convolutional neural networks (CNNs), which have become a powerful tool to solve many problems in the field of computer vision. DeepPano, a variant of CNN, converts each 3D shape into a panoramic view and shows excellent performance. It is worth paying attention to the fact that both serious information loss and redundancy exist in the processing of DeepPano, which limits further improvement of its performance. In this work, we propose a more effective method to preprocess 3D shapes also based on a panoramic view, similar to DeepPano. We introduce a novel method to expand the training set and optimize the architecture of the network. The experimental results show that our approach outperforms DeepPano and can deal with more complex 3D shape recognition problems with a higher diversity of target orientation.

A Novel Dual-Loop Disturbance Observer-Based Attitude Control for a Space-Based Observation Microsatellite

Abstract: Aiming at strong coupling and nonlinear dynamic equations for a space-based observation satellite, a sliding mode controller with feed-forward compensation is proposed in this paper. The theorem of moment of momentum is applied to formulate the exact nonlinear dynamic equations of a multibody satellite. On this basis, sliding-mode control-based, dual-loop forward-feed compensation control is used to control the attitude of the space-based observation microsatellite. By comparing with the conventional control method, simulation results demonstrate that the proposed control method has superior performance in terms of suppression from external disturbances and vibration. Better dynamic and static performance indices than the conventional control method are achieved.

Integrating Physics-Based Modeling with Machine Learning: A Survey

Abstract: In this manuscript, we provide a structured and comprehensive overview of techniques to integrate machine learning with physics-based modeling. First, we provide a summary of application areas for which these approaches have been applied. Then, we describe classes of methodologies used to construct physics-guided machine learning models and hybrid physics-machine learning frameworks from a machine learning standpoint. With this foundation, we then provide a systematic organization of these existing techniques and discuss ideas for future research.

Aircraft Active Flutter Suppression: State of the Art and Technology Maturation Needs

Abstract: Active flutter suppression, which is a part of the group of flight vehicle technologies known as active controls, is an important contributor to the effective solution of aeroelastic instability pr...