• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.177-182
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• 1994

In this paper, an output feedback adaptive variable structure control scheme is presented for stabilization of large scale power systems. An additional input signal which is called a power system stabilizer(PSS) is needed to improve the stability of a power system and to maintain the synchronization of generators. The proposed PSS scheme does not require a priori knowledge of uncertainty bounds. It is guaranteed that the closed-loop system is globally uniformly ultimately bounded by the Lyapunov stability theory. Simulation results for a multimachine power system are given to show the feasibility of the proposed scheme and the superiority of the proposed PSS in comparison with the conventional lead-lag PSS of PID-type.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.278-287
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• 2005

In this paper a new excitation control scheme that improves the transient stability of multi machine power systems is proposed. To this end the backstepping technique is used to transform the system to a suitable partially linear form. On this system, a combination of both feedback linearization and adaptive control techniques are used to confront the nonlinearities. As shown in the paper, the resulting nonlinear control law ensures the uniform boundedness of all the state and estimated variables. Furthermore, it is proven that all the error variables are uniformly ultimately bounded (DUB) i.e. they converge to arbitrarily selected small regions around zero in finite-time. Simulation tests on a two generator infinite bus power system demonstrate the effectiveness of the proposed control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.553-556
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• 2005

A novel sufficient condition of discretized equivalent control based sliding mode controller (SMC) for a second-order system with external disturbance to be globally uniformly ultimately bounded (GUUB) is proposed. The proposed stability condition guarantees that the system state is always GUUB in the presence of disturbance. The ultimate bounds of the system state variables are also derived.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1103-1109
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• 2008

Since the flexible joint robots with motor dynamics are represented by the fifth-order nonlinear sγstem, it is difficult and complex to design the controller for electrically driven flexible-joint (EDFJ) robots. In this paper, we propose a simple adaptive control method to solve this problem. It is assumed that the model uncertainties of the robots dynamics, joint flexibility, and motor dynamics are unknown. For the simple control design, the dynamic surface design method is applied, and all uncertainties in the robot and motor dynamics are compensated by using the adaptive function approximation technique. It is proved that all signals in the controlled closed-loop system are uniformly ultimately bounded. Simulation results for three-link EDFJ manipulators are provided to validate the effectiveness of the proposed control system.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.371-373
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• 1992

This note proposes a novel robust adaptive control algorithm for systems with unknown disturbances by introducing an additional term in the control input. This additional term is easily implementable by estimating the upper bound of the unknown disturbances. By this term, the output error can be made to be uniformly ultimately bounded in a desired region via Lyapunov second stability theorem when the relative degree of system is one.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.42-47
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• 2014

This paper investigates an adaptive approximation design problem for the tracking control of output-constrained non-affine pure-feedback systems. To satisfy the desired performance without constraint violation, we employ a barrier Lyapunov function which grows to infinity whenever its argument approaches some limits. The main difficulty in dealing with pure-feedback systems considering output constraints is that the system has a non-affine appearance of the constrained variable to be used as a virtual control. To overcome this difficulty, the implicit function theorem and mean value theorem are exploited to assert the existence of the desired virtual and actual controls. The function approximation technique based on adaptive neural networks is used to estimate the desired control inputs. It is shown that all signals in the closed-loop system are uniformly ultimately bounded.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.1-12
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• 2004

This paper presents an adaptive fuzzy backstepping (AFB) controller for a single-link flexible joint robot in the Presence of Parametric uncertainties and external disturbances. Adaptive fuzzy logic systems are used as universal approximators to counteract the model uncertainties coming from robot dynamics and to compensate for the nonlinearities coming from adaptive backstepping method. The approach suggested herein does not require neither an additional supervisory nor a robustifying controller and guarantees that tracking error is uniformly ultimately bounded (UUB) within a sufficiently small residual set. Finally, a simulation result is given to demonstrate the robust tracking performance of proposed design method.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1759-1760
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• 2008

This paper proposes a neural network(NN)-based adaptive sliding mode controller for discrete-time nonlinear systems. By using disturbance estimation technique, a sliding mode controller is designed, which forces the sliding variable to be zero. Then, NN compensator with hidden-layer-to-output-layer weight update rule is combined with sliding mode controller in order to reduce the error of the estimates of both disturbances and nonlinear functions. The whole closed loop system rejects disturbances excellently and is proved to be ultimately uniformly bounded(UUB) provided that certain conditions for design parameters are satisfied.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.748-752
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• 2015

We present an output feedback controller for a class of nonlinear systems with uncertain nonlinearity and sensor noise. The sensor noise has both a finite constant component and a time-varying component such that its integral function is finite. The new design and analysis method is based on the matrix inequality approach. With our proposed controller, the states and output can be ultimately bounded even though the structure of nonlinearity is more general than that in the existing results.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.223-233
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• 2008

A new output feedback controller design approach for flexible-joint (FJ) robots via the observer dynamic surface design technique is presented. The proposed approach only requires the feedback of position states. We first design an observer to estimate the link and actuator velocity information. Then, the link position tracking controller using the observer dynamic surface design procedure is developed. Therefore, the proposed controller can be simpler than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop system are uniformly ultimately bounded. Finally, the simulation results of a three-link FJ robot are presented to validate the good position tracking performance of the proposed control system.