• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.422-427
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• 1994

In this paper, we propose a new design approach of a two-degrees-of-freedom compensator which assures the robust stability. First of all, we clarify the internal structure of the generalized two-degrees-of-freedom compensator. By adopting this structure, we can make a bridge between the generalized controller and the disturbance observer based controller, Secondly, based on the clarified structure we derive a robust stability condition, and propose a design algorithm of free parameter taking the condition into account. The proposed design algorithm is easy to implement and, as a result, we obtain lower order free parameter then that of the conventional design algorithm.. Thirdly, we show by adopting an appropriate coprime factorization that the clarified structure can also be regarded as an extended version of the conventional PID compensator. Finally, we apply the proposed algorithm to a three-degrees-of freedom direct drive robot, and show some experimental results to verify the effectiveness of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.80-84
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• 2002

This paper proposes a decentralized control technique for 2-dimensional experimental helicopter systems. The decentralized control technique is especially suitable in large-scale control systems. We derive the stabilization condition for the interconnected Takagi-Sugeno (TS) fuzzy system using the rigorous tool-Lyapunov stability criterion and formulate the controller design condition in terms of linear matrix inequality (LMI). To demonstrate the feasibility of the proposed method, we include the experiment result as well as a computer simulation one, which strongly convinces us the applicability to the industry.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.304-306
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• 1993

In this paper, the authors show a link between a heuristic controller used in industry and a theoretical generalized controller. First, we clarify the internal structure of the generalized two-degree-of-freedom controller which yields a link between the theoretical researches and the practical applications. Secondly, we indicate how to blend identification and control together without any modification of the controller. This is in fact the problem of closed-loop identification. Thirdly, we propose a design technique of a free parameter taking into account a robust stability based on the information obtained from the identification. Finally, we apply the proposed algorithm to trajectory control of DD robot.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.117-122
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• 1992

The fuzzy-neural hybrid control system utilizing the fuzzy-neural network(FNN) will be presented in this paper. The basic structure of the controller is the parallel combination of a conventional P-controller and a FNN. Such a combination can guarantee the stability of a plant at initial stage before the rules are completely created. And a method how to automatically tunning the parameters of the FNN will be proposed with error back-propagation(BP) algorithm. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a two DOF robot manipulator.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.54-60
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• 2010

This paper presents a new algorithm for determining generator operation point for maintaining stability considering generator faults in Jeju-Haenam HVDC system. As the HVDC system consumes reactive power for the transmission of active power substantially, compensation of reactive power is essential. And the HVDC system is operated on frequency control mode. That is to say, the HVDC system almost manages system frequency. Therefore, we recognized that the Jeju system could be unstable if the reactive power consumed by the HVDC is insufficient when out-of-step occurs with large generators. When the solution of power flow analysis does not converge due to the unstable system phenomenon, we have difficulty in establishing countermeasures as the post-fault information is not available. In this paper, for the purpose of overcoming this difficulty in establishing countermeasures, we introduce the CPF(Continuation Power Flow) algorithm. This paper suggests an algorithm for calculating the output limitation of the generator to maintain the stability in case of generator fault in the Jeju system.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1132-1137
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• 2007

This paper describes a Unified Chassis Control (UCC) strategy to prevent vehicle rollover by integrating individual modular chassis control systems such as Electronic Stability Control (ESC) and Continuous Damping Control (CDC). The UCC threshold is determined from a rollover index computed by estimated roll angle, roll rate and measured lateral acceleration. A direct yaw moment control method is used to design the ESC based on a 2-D bicycle model. Similarly, the CDC is designed based on a 2-D roll model using a direct roll moment control method. The performance of the proposed UCC scheme is investigated and compared to that of modular chassis controllers through computer simulations using a validated vehicle simulator. It is shown that the proposed the UCC can lead to improvements in vehicle stability and efficient actuation of chassis control systems.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.898-906
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• 2002

Antilock Brake System (ABS) is designed to prevent wheels from being locked-up under emergency braking of a vehicle. Therefore it improves directional stability of the vehicle, shortens stopping distance, and enhances maneuvering during braking, regardless of road conditions. Hardware In-the-Loop Simulation (HILS) is an effective tool for design Performance evaluation and test of vehicle subsystems such as ABS, active suspension, and steering systems. This paper describes a HILS model for ABS/ ASR(Acceleration Slip Regulation) system applications. A fourteen degrees-of-freedom vehicle dynamics model is simulated in an alpha-chip processor board. The proposed HILS system is tested with a basic ABS control algorithm. The design and implementation of HILS system for the ABS ECU(Electronic Control Unit) development of commercial vehicle are presented. The results show that the proposed HILS system can be used to test the performance, stability, and reliability of a vehicle under braking.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1486-1491
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• 2005

In this paper, a robust H${\infty}$ stabilization problem to a uncertain fuzzy systems with time-varying delay via static output feedback is investigated. The Takagi-Sugeno (T-S) fuzzy model is employed to represent uncertain nonlinear systems with time-varying delayed state, which is a continuous-time or discrete-time system. Using a single Lyapunov function, the globally asymptotic stability and disturbance attenuation of the closed-loop fuzzy control system are discussed. Sufficient conditions for the existence of robust H${\infty}$controllers are given in terms of linear matrix inequalities.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1728-1729
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• 2007

This paper presents an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for a full dynamics of a nonlinear flight system. It is assumed in this paper that model uncertainties such as structured and unstrutured uncertainties and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate model uncertainties of the nonlinear flight system, and an adaptive DSC technique is extended for disturbance attenuation of the nonlinear flight system. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance from external disturbances can be obtained. Finally, we perform the simulation for the nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.