• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.8
• /
• pp.792-804
• /
• 1990

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.4
• /
• pp.501-509
• /
• 2010

A floating crane is a crane-mounted ship and is used to assemble or to transport heavy blocks in shipyards. In this paper, the static and dynamic response of a floating crane and a heavy block that are connected using elastic booms and wire ropes are described. The static and dynamic equations of surge, pitch, and heave for the system are derived on the basis of flexible multibody system dynamics. The equations of motion are fully coupled and highly nonlinear since they involve nonlinear mass matrices, elastic stiffness matrices, quadratic velocity vectors, and generalized external forces. A floating frame of reference and nodal coordinates are employed to model the boom as a flexible body. The nonlinear hydrostatic force, linear hydrodynamic force, wire-rope force, and mooring force are considered as the external forces. For numerical analysis, the Hilber-Hughes-Taylor method for implicit integration is used. The dynamic responses of the cargo are analyzed with respect to the results obtained by static and numerical analyses.

• International Journal of Automotive Technology
• /
• v.6 no.1
• /
• pp.29-35
• /
• 2005

The structural integrity of either a passenger car or a light truck is one of the basic requirements for a full vehicle engineering and development program. The results of the vehicle product performance are measured in terms of ride and handling, durability, Noise/Vibration/Harshness (NVH), crashworthiness, and occupant safety. The level of performance of a vehicle directly affects the marketability, profitability and, most importantly, the future of the automobile manufacturer. In this study, the Virtual Proving Ground (VPG) approach has been developed to simulate dynamic nonlinear events as applied to automotive ride & handling. The finite element analysis technique provides a unique method to create and analyze vehicle system models, capable of including vehicle suspensions, powertrains, and body structures in a single simulation. Through the development of this methodology, event-based simulations of vehicle performance over a given three-dimensional road surface can be performed. To verify the predicted dynamic results, a single lane change test was performed. The predicted results were compared with the experimental test results, and the feasibility of the integrated CAE analysis methodology was verified.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2003.04a
• /
• pp.61-68
• /
• 2003

Cable domes deform very largely because of the characteristics of flexible hybrid system and pre-tension, and include geometrical non-linearity in those structural behavior. Especially wind load is more dominant than seismic loads, because cable domes are flexible structures whose stiffness is very small and self-weight is very light. Therefore, in this paper, Modified Stiffly Stable Method is applied to analyze the nonlinear dynamic behavior of cable domes and compared these results with ones of Newmark-β Method which is generally used. The Seoul Olympic Gymnastic Arena is taken as an numerical example and three kinds of models with giving each different intensity of pre-tension are selected. And dynamic nonlinear behavior of cable domes are analyzed by artificial spectrum of wind velocity wave which is similar to actual wind loads.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.3
• /
• pp.65-71
• /
• 1997

With the emergence of neural network, there is a revived interest in identification of nonlinear systems. So in this paper, to identify unknown nonlinear systems dynamically we propose DPNN(Dynamic Polynomial Neural Network) using GMDH (Group Method of Data Handling) algorithm. The dynamic system identification using GMDH consists of applying a set of inputloutput data to train the network by dynamically computing the necessary coeffici1:nt sets. Then, MRAC(Mode1 Reference Adaptive Control) is designed to control nonlinear systems using DPNN. In the result, we can see that the modelling and control using DPNN work well by computer simulation.

• Structural Engineering and Mechanics
• /
• v.43 no.2
• /
• pp.163-177
• /
• 2012

This paper presents a LMI(linear matrix inequality)-based fuzzy approach of modeling and active vibration control of geometrically nonlinear flexible plates with piezoelectric materials as actuators and sensors. The large-amplitude vibration characteristics and dynamic partial differential equation of a piezoelectric flexible rectangular thin plate structure are obtained by using generalized Fourier series and numerical integral. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the nonlinear structural system, which combines the fuzzy inference rule with the local linear state space model. A robust fuzzy dynamic output feedback control law based on the T-S fuzzy model is designed by the parallel distributed compensation (PDC) technique, and stability analysis and disturbance rejection problems are guaranteed by LMI method. The simulation result shows that the fuzzy dynamic output feedback controller based on a two-rule T-S fuzzy model performs well, and the vibration of plate structure with geometrical nonlinearity is suppressed, which is less complex in computation and can be practically implemented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.204-210
• /
• 1998

This paper discusses an on-line fuzzy dynamic model(FDM) identification of nonlinear processes for the design of fuzzy model based fault detection and isolation(FDI). The dynamic behavior of a nonlinear process is represented by a fuzzy aggregation of a set of local linear models. The identification is divided into two procedures. The first is the off-line identification of membership function. The second is the on-line identification of the local linear models. Then, we propose a residual generation scheme based on the parameters of local linear models and show that the scheme can be used for the design of FDI

• Proceedings of the KAIS Fall Conference
• /
• 2007.11a
• /
• pp.81-84
• /
• 2007

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.125.3-125
• /
• 2001

Recently, aircraft is designed to have high maneuverable at high angle of attack. However, it is very hard to obtain the accurate dynamic model for the high performance, because aerodynamic characteristics are nonlinear and include a lot of uncertainties. Therefore, nonlinear controller without considering uncertainties may degrade the control system performance. On this paper, to overcome these defects, the neural networks based adaptive nonlinear controller is proposed making use of the backstepping technique. Neural networks are implemented to guarantee robustness to uncertainties caused by aerodynamic coefficients variation. The main feature of the proposed controller is that the adaptive controller is developed under the assumption ...

• International Journal of Control, Automation, and Systems
• /
• v.3 no.2
• /
• pp.244-251
• /
• 2005

In this paper, we study the problem of stabilizing a general nonlinear control system by means of gradient descent control method which is a dynamic feedback control law. In this method, the general nonlinear control system can be considered as an affine nonlinear control systems. Then by using Sontag's formula we investigate the stability (asymptotic) of the general nonlinear control system.