• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.346-352
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• 2016

This paper proposes an adaptive robust control method for an acrobot system in the presence of input disturbance. The acrobot system is a typical example of the underactuated system with complex nonlinearity and strong dynamic coupling. Also, disturbance can cause limit cycle phenomenon which appears in the acrobot system around the desired unstable equilibrium point. To minimize the effect of the disturbance, we apply a fuzzy disturbance estimation method for the swing-up and balancing control of the acrobot system. In this paper, both disturbance observer and controller for the acrobot system are designed and verified through mathematical proof and simulations.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.20-27
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• 1994

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an improved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing forces coming from the difference between the actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.321-325
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• 1988

The objective of this study is to develop a microcomputer-based adaptive controller for an electro hydraulic velocity control system subjected to the variation of system parameters. The step response performance of the system with the adaptive controller is investigated for the variation of the external load torque, the moment of inertia and the reference inputs, and compared with that obtained by PID controller whose gains are constant. The experimental results show that this proposed model reference adaptive controller is robust to the variation of system parameters and yield much better control performance compared with the conventionel PID controller.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.157-163
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• 2014

In this paper, a robust MRAC (model reference adaptive control) scheme is applied to control an electrohydraulic positioning system under various loads. The inverse dead-zone compensator in the control system cancels out the dead-zone response, and an integrator added to the controller provides good position-tracking ability. LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) closed-loop model is used as the reference model for learning the MRAC system. LQG/LTR provides a systematic technique to design the linear controller that optimizes the objective function using some compromise between the control effort and the system performance in the frequency domain. Different external load tests are performed to investigate the effectiveness of the designed MRAC system in real time. The experimental results show that the tracking performance of the proposed system is highly accurate, which offers considerable robustness even with a large change in the load.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.294-300
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• 2009

The neural network with radial basis function is introduced for position tracking control of AC servo drive with the existence of system uncertainties. An adaptive robust term is applied to overcome the external disturbances. The proposed controller is implemented on a high performance digital signal processing DSP TMS320C6713-300. The stability and the convergence of the system are proved by Lyapunov theory. The validity and robustness of the controller are verified through simulation and experimental results

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2441-2443
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• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1688-1691
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• 1997

In the time-invarient system, the adaptive controller was designed for the non-tracking error in the 1980's. In this study, the Model Reference Adaptive Control using on-line processing method is used to identify the coefficients of the model, and the Robust Controller (H.inf.) is designed to stabilize the rigid body and the flexible body of satellite, which can be perturbed due to disturbance, etc. The result obtained by H.inf. controller is compared with that of the PI(Proportional and Intergation) controller which is commonly used for stabilizing satellite.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.22-30
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• 1993

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th orther single-input single-output systems of which state variables can be observable are also studied and utilized for the design of new-type controllers. We drived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1424-1429
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• 1990

This paper presents an indirect adaptive control scheme for discrete linear systems whose parameters are not necessrily slowly varying. It is assumed that system parameters are modelled as linear combinations of known bounded functions with unknown constant coefficients. Unknown coefficients are estimated using a recursive least squares algorithm with a dead zone and a forgetting factor. A control law which makes the estimated model exponentially stable is constructed. With this control law and a state observer, all based on the parameter estimates, it is shown that the resulting closed-loop system is globally stable and robust to bounded external disturbances and small unmodelled plant uncertainties.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.3
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• pp.119-128
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• 2005

In this paper, an robust adaptive backstepping controller is proposed for the chaos system with disturbances. This controller will be applicable to the chaos system of strict-feedback form and utilize the saturation function for decreasing the effect of disturbances derived from unmodelled dynamics and external noise. It shows that backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the proposed controller.