• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.441-444
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• 2003

Network uncertainties such as data loss and time delay can vary the stability property of networked control system. Therefore, these uncertainties must be considered first in designing networked control system. In this paper, we present a new stability analysis method of networked control system with data loss and time delay. The proposed method can determine maximum allowable time delay and minimum allowable transmission rate that preserves stability performance of networked control system. The results of the simulation validate effectiveness of our stability analysis method.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.320-328
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• 2016

The introduction of renewable energy sources into the AC grid can change and weaken the strength of the grid, which will in turn affect the stability and robustness of the doubly-fed induction generator (DFIG) wind farm. When integrated with weak grids, the DFIG wind turbine with vector power control often suffers from poor performance and robustness, while the DFIG wind turbine with synchronized control provides better stability. This paper investigates the critical short circuit ratios of DFIG wind turbine with vector power control and synchronized control, to analyze the stability boundary of the DFIG wind turbine. Frequency domain methods based on sensitivity and complementary sensitivity of transfer matrix are used to investigate the stability boundary conditions. The critical capacity of DFIG wind farm with conventional vector power control at a certain point of common coupling (PCC) is obtained and is further increased by employing synchronized control properly. The stability boundary is validated by electromagnetic transient simulation of an offshore wind farm connected to a real regional grid.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.903-909
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• 2015

This article presents an integrated chassis control with electronic stability control (ESC) and active front steering (AFS) under saturation of front lateral tire force. Regardless of the use of AFS, the front lateral tire forces can be easily saturated. Under the saturated front lateral tire force, AFS cannot be effective to generate a control yaw moment needed for the integrated chassis control. In this paper, new integrated chassis control is proposed in order to limit the use of AFS in case the front lateral tire force is saturated. Weighed pseudo-inverse control allocation (WPCA) with variable weight is adopted to adaptively use the AFS. To check the effectiveness of the proposed scheme, simulation is performed on a vehicle simulation package, CarSim. From simulation, the proposed integrated chassis control is effective for vehicle stability control under saturated front lateral tire force.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.78-83
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• 2011

Traditional autopilot design requires an accurate aerodynamic model and relies on a gain schedule to account for system nonlinearities. This paper presents the control architecture applied to a dynamic model inversion at a single flight condition with an on-line neural network (NN) in order to regulate errors caused by approximate inversion. This eliminates the need for an extensive design process and accurate aerodynamic data. The simulation results using a developed full nonlinear 6 degree of freedom model are presented. This paper also presents the stability evaluation for control systems to which NNs were applied. Although feedback can accommodate uncertainty to meet system performance specifications, uncertainty can also affect the stability of the control system. The importance of robustness has long been recognized and stability margins were developed to quantify it. However, the traditional stability margin techniques based on linear control theory can not be applied to control systems upon which a representative non-linear control method, such as NNs, has been applied. This paper presents an alternative stability margin technique for NNs applied to control systems based on the system responses to an inserted gain multiplier or time delay element.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.411-418
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• 2006

There are mainly two types of bang-bang controllers for nominal linear time-invariant (LTI) system. Optimal bang-bang controller is designed based on optimal control theory and suboptimal bang-bang controller is obtained by using Lyapunov stability condition. In this paper, the suboptimal bang-bang control method is extended to LTI system involving both control input saturation and structured real parameter uncertainties by using Lyapunov robust stability condition. Two robust optimal bang-bang controllers are derived by minimizing the time derivative of Lyapunov function subjected to the limit of control input. The one is developed based on the classical quadratic stability(QS), and the other is developed based on the affine quadratic stability(AQS). And characteristics of the two controllers are compared. Especially, bounds of parameter uncertainties which theoretically guarantee robust stability of the two controllers are compared quantitatively for 1DOF vibrating system. Moreover, the validity of robust optimal bang-bang controller based on the AQS is shown through numerical simulations for this system.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.672-680
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• 2012

This paper proposes the control strategy of the shunt Flexible AC Transmission System (FACTS) devices to improve transient stability in multimachine power system. The multimachine power system has high nonlinear response after severe disturbance. The concept of Lyapunov energy function is applied to derive nonlinear control strategy and it was found that the time derivative of line voltage is not only can apply to control the shunt FACTS devices in multimachine system but also is locally measurable signal. The fuzzy logic control is also applied to overcome the uncertainty of various disturbances in multimachine power system. This paper presents the method of investigating the effect of the shunt FACTS devices on transient stability improvement. The proposed control strategy and the method of simulation are tested on the new England power system. It was found that the shunt FACTS devices based on the proposed nonlinear control strategy can improve transient stability of multimachine power system.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.37-43
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• 2013

This paper describes an investigation into coordinated control of electronic stability control (ESC) and active roll control system (ARS). The coordinated control is suggested to improve the vehicle stability and agility features by yaw rate control. The proposed integrated chassis control algorithm consists of a supervisor, control algorithms, and a coordinator. The supervisor monitors the vehicle status and determines desired vehicle motions such as a desired yaw rate and desired roll motion based on control modes to improve vehicle stability. According to the corresponding the desired vehicle dynamics, the control algorithm calculated a desired yaw moment and desired roll moment, respectively. Based on the desired yaw moment and the desired roll moment, the coordinator determines the brake pressures and the ARC motor torques based on control strategies. Closed loop simulations with a driver-vehicle-controller system were conducted to investigate the performance of the proposed control strategy using CarSim vehicle dynamics software and the integrated controller coded using Matlab/Simulink.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.4
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• pp.470-477
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• 2000

The states of control loops in existing actual systems are changed according to time varying conditions of controllest process and other system components. Adjusting control parameters properly at site which is performed generally by Ziegler & Nichols mthod is important for safe and efficient operation, but the method may require much time to adjust and not easy to inexperienced engineers. This study is aimed to propose more handy method to adjust control parameters by plotting operating conditions on the space of adjusting parameters. One loop of model control system without perturbation condition has been adopted and its stability limit was plotted on the coordinates of Gain and Integral time which was acquired after analyzing Nyquist diagrams and time domain responses. The result showed that the sets of adjusting parameters according to critical stability and proper stability could be acquired reasonably through both responses and the curves on parameter space revealed available patterns for the purpose of easy maintenance of control characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.734-740
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• 1987

Various kinds of predictive control design methods such as MAC(Model Algorithmic Control), DMC(Dynamic Matrix Control), MC(Extended Horizon Adaptive Control), GPC(Generalized Predictive Control), RHTC(Receding Horizon Tracking Controller), and PVC(PreView Controller) are surveyed and compared in this paper. In addition, stability properties of these control laws known to date are summarized and some new stability results are presented.

• KIEE International Transaction on Systems and Control
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• v.12D no.1
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• pp.43-50
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• 2002

In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.