• Journal of applied mathematics & informatics
• /
• v.25 no.1_2
• /
• pp.293-304
• /
• 2007

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1607-1610
• /
• 1991

It is difficult to design the controller of an induction motor because of its non-linearity and high order dynamics. But it is possible to get reduced order system using the theory of singular pertubation because the dynamics of induction motor consists of fast stable mode and slow one. On the other hand, the sliding mode control is well-known for its performance of robustness. This paper deals with the sliding mode controller of induction motors based on the reduced order system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.19 no.1
• /
• pp.80-86
• /
• 2005

This paper proposes a design method of PID controller for achieving the desired specifications in the frequency domain via the reduced model of a high-order model with time delay. The proposed method identifies the parameter vector of PID controller from a linear system that develops from rearranging the two dimensional input matrices and output vectors obtained from the frequency bounds. Four examples are given to illustrate the feasibilities of the suggested schemes.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.3
• /
• pp.384-389
• /
• 2004

Recently a method of model reduction for discrete systems has been proposed in the literature based on a new impulse response Gramian. In this method, the system matrix$A_r$ of a reduced model is computed by approximating the reduced-order impulse response Gramian. The remaining matrices $b_r$ and $c_r$ are obtained so that various initial Markov parameters and time-moments of the original system are preserved in the reduced model. In this paper a different approach is presented based on the recursive relationship among the impulse response Gramians.

• Korean Journal of Computational Design and Engineering
• /
• v.8 no.2
• /
• pp.109-114
• /
• 2003

In order to develop the reduced tire modal model for analyzing a full tire model, the Craig-Bampton method is utilized in this paper. When the tire contacts the road, the Abaqus solver extracts the condensed stiffness, coupled mass and mode shape matrix about the node, which contacts the road. The Abaqus full tire model is reduced using the substructure method utilizing Craig-Bampton algorithm. Then, the extracted matrices are interfaced with the superelement, which is fed to the Nastran reduction algorithm. Eventually, the reduced tire model is verified from experiment and various reduction parameters (i.e. modal number, reduction point, etc.) are studied for the effectiveness of the proposed paper.

• International Journal of Aeronautical and Space Sciences
• /
• v.18 no.4
• /
• pp.651-661
• /
• 2017

A truss-braced wing (TBW) aircraft has recently received increasing attention due to higher aerodynamic efficiency compared to conventional cantilever wing aircraft. For conceptual TBW aircraft design, we developed a propulsion-and-airframe integrated design environment by replacing a semi-empirical turbofan engine model with a thermodynamic cycle-based one built upon the numerical propulsion system simulation (NPSS). The constructed NPSS model benefitted TBW aircraft design study, as it could handle engine installation effects influencing engine fuel efficiency. The NPSS model also contributed to broadening TBW aircraft design space, for it provided turbofan engine design variables involving a technology factor reflecting progress in propulsion technology. To effectively consolidate the NPSS propulsion model with the TBW airframe model, we devised a rapid, approximate substitute of the NPSS model by reduced-order modeling (ROM) to resolve difficulties in model integration. In addition, we formed an artificial neural network (ANN) that associates engine component attributes evaluated by object-oriented weight analysis of turbine engine (WATE++) with engine design variables to determine engine weight and size, both of which bring together the propulsion and airframe system models. Through propulsion-andairframe design space exploration, we optimized TBW aircraft design for fuel saving and revealed that a simple engine model neglecting engine installation effects may overestimate TBW aircraft performance.

• Smart Structures and Systems
• /
• v.13 no.1
• /
• pp.99-109
• /
• 2014

The goal of any Model Order Reduction (MOR) technique is to build a model of order lower than the one of the real model, so that the computational effort is reduced, and the ability to estimate the input-output mapping of the original system is preserved in an important region of the input space. Actually, since only a subset of the input space is of interest, the matching is required only in this subset of the input space. In this contribution, the consequences on the achieved accuracy of adopting different reduction technique patterns is discussed mainly with reference to a linear case study.

• Smart Structures and Systems
• /
• v.18 no.1
• /
• pp.1-16
• /
• 2016

Model Order Reduction (MOR) denotes the theory by which one tries to catch a model of order lower than that of the real model. This is conveniently pursued in view of the design of an efficient structural control scheme, just passive within this paper. When the nonlinear response of the reference structural system affects the nature of the reduced model, making it dependent on the visited subset of the input-output space, standard MOR techniques do not apply. The mathematical theory offers some specific alternatives, which however involve a degree of sophistication unjustified in the presence of a few localized nonlinearities. This paper suggests applying standard MOR to the linear parts of the structural system, the interface remaining the original unreduced nonlinear components. A case study focused on the effects of a helicopter land crash is used to exemplify the proposal.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.6
• /
• pp.465-470
• /
• 2001

This paper considers a new weighed model reduction method using block diagonal solutions of Lyapunov inequalities. With the input and/or output weighting function, the stability of the reduced order system is guaranteed and an a priori error bound is proposed. to achieve this after finding the solutions of two Lyapunov inequalities and balancing the full order system, we find the reduced order systems using the direct truncation and the singular perturbation approximation. The proposed method is compared with other existing methods using numerical examples.

• Proceedings of the Korean Biophysical Society Conference
• /
• 2003.06a
• /
• pp.26-26
• /
• 2003

The backbone dynamics of ketosteroid isomerase, a homodimeric enzyme with 125 amino acid residues per subunit, has been studied in the presence/absence of a steroid ligand and 5％ trifluoroethanol (TFE) by $^{15}$ M relaxation measurements. The relaxation data were analyzed using the model-free formalism to extract the model-free parameters (S$^2$, $\tau$$_{e}$, and R$_{ex}$ ). The results show that a large number of the residues, particularly those involved in the dimer interaction, exhibit reduced order parameters (S$^2$) in the steroid-bound enzyme, indicating the increased high-frequency (pico- to nanosecond) motions in the interface region upon ligand binding. The results also show that that the presence of 5 ％ TFE in free enzyme causes little change or slight increase in the order parameters for a number of residues in the dimer interface region. However, the majority of the residues in free enzyme exhibit reduced order parameters in the presence of 5 ％ TFE, indicating that the increase in entropy is partially responsible for the increased stability of KSI by 5％ TFE.E.E.