• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.76-78
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• 2009

This paper considers the problem of global adaptive regulation for a class of nonlinear systems which have multiple unknown virtual control coefficient. By using a new parameter estimator and backstepping technique, we design a smooth state feedback control law, parameter update laws that estimate the unknown virtual control coefficients, and a continuously differentiable Lyapunov function which is positive definite and proper.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.195-198
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• 1997

This paper proposes the effective compensation method of the rotor time constant of induction motor. An indirect vector control method is highly dependent on the motor parameters. To solve the problem of performance degradation due to parameter variation in an indirect vector control of induction motor, we compensate the rotor time constant by current error feedback. The proposed method is a simple on-line rotor time constant compensation method using the information from terminal voltages and currents. As the current error, difference between current command and estimated current, approaches to zero, the value of rotor time constant in an indirect vector controller follows the real value of induction motor. This scheme is valid transient region as well as steady state region regardless of low or high speed. This method is verified by computer simulation. For this, we constructed the simulation model of induction motor, indirect vector controller and current regulated PWM (CRPWM) voltage source inverter (VSI) using SIMULINK in MATLAB.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.276-280
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• 2001

In this paper, an approach to the design of negative impedance stabilizing controllers for PWM DC/DC converters that are used in DC switching. power supplies with constant power loads is presented. The control approach is based on the feedback linearization technique. Because of the negative impedance destabilizing characteristics of constant power loads, classical linear control methods have stability limitations around the operating points. However, the proposed stabilizing technique improves large-signal stability and dynamic responses. The proposed controllers are simulated and their responses under different operations are studied. Stability of the control technique is also verified using the second theorem of Lyapunov.

• Journal of Power System Engineering
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• v.10 no.3
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• pp.97-103
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• 2006

In this study, a position trajectory tracking control algorithm is proposed for a pneumatic artificial muscle driving apparatus composed of a actuator which imitates the muscle of human, a position sensor and a control valve. The controller applied to the driving apparatus is composed of a state feedback controller and disturbance observer. The feedback controller which feeds back position, velocity and acceleration is derived from the linear model of pneumatic artificial muscle driving apparatus. The disturbance observer is designed to improve trajectory tracking performance and to reduce the effect of model discrepancy. The effectiveness of the designed controller is proved by experiments and the experimental results show that the pneumatic artificial muscle driving apparatus with the proposed control algorithm tracks given position reference inputs accurately.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.116-120
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• 2000

This paper presents a method to assign robustly the closed loop system's poles in a specified disk by a state feedback for a linear time invariant system with structured or unstructured uncertainties. THe proposed robust design procedure includes two steps. Firstly, the perturbed closed loop matrix $A_{cl p}$ = $A_{cl}$ + Δ$A_{cl}$ is rearranged such that it is a function of the nominal closed loop matrix $A_{cl}$. Hence, we can control the positions of the perturbed closed loop poles by choosing $A_{cl}$ appropriately. Secondly, the feedback control law F that assigns the closed loop poles of the perturbed system in a specified disk is determined from the equation $A_{cl}$ = A + BF. A procedure for finding F is proposed based on partitioning every matrix of the equation $A_{cl}$ = A + BF in the horizontal direction.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.18-18
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• 2000

In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network are provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shows that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.39-54
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• 2004

We developed an automatic blood pressure control system to maintain the blood pressure of patients at a substantially low level during a surgical operation. The developed system discharges two functions, continuous feedback control of the mean arterial pressure (MAP) by a state-predictive servo controller and risk control based on the inference by fuzzy-like logics and rules using measured data. Twenty-eight clinical applications were made beginning in November 1995, and the effects of the automatic blood pressure control on the operation time and on bleeding were assessed affirmatively by means of Wilcoxon testing. This paper essentially reports the engineering details of the control system.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.171-177
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• 2003

In this paper, we investigate a robust $H_{\infty}$ state feedback control technique for continuous time bilinear systems with an additive disturbance input. The nonlinear robust $H_{\infty}$control for bilinear systems requires a solution to the state dependent algebraic Riccati equation (SDARE). We present a new robust $H_{\infty}$control technique based on the successive approximation method for solving the SDARE by converting bilinear systems into time-varying linear systems. The proposed control method guarantees robust stability for closed loop bilinear systems. The proposed algorithm is verified by numerical examples.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.236-248
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• 2017

A direct stator flux vector control scheme in discrete-time domain is proposed in this paper for the interior permanent magnet synchronous motor (IPMSM) drive to remove the proportional-integral (PI) controller from the direct torque control (DTC) scheme applied to IPMSM and to obtain faster dynamic response and lower torque ripple output. The output of speed outer loop is used as the desired torque angle instead of the desired torque in the proposed scheme. The desired stator flux vector in dq coordinate is calculated with a given amplitude. The state-space equations in discrete-time for IPMSM are established, the actual stator flux vector is estimated in deadbeat manner by a full-order state observer, and then the closed-loop control is achieved by the pole placement. The stator flux error vector is utilized to calculate the reference stator voltage vector. Extracting the angle position and amplitude from the estimated stator flux vector and estimating the output torque are eliminated for the direct feedback control of the stator flux vector. The proposed scheme is comparatively investigated with a PI-SVM DTC scheme by experiment results. Experimental results show the feasibility and advantages of the proposed control scheme.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.88-94
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• 1997

This paper presents the sliding mode observer-model following (SMO-MF) power system stabilizer(PSS) for unmeasurable state variables. This SMO-MF PSS is obtained by combining the sliding mode-model following (SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). The control input of the proposed MO-MF PSS is derived by Lyapunov's second method to determine a control input that keeps the system stable for unmeasurable plant state variables. Simulation results show that the proposed SMO-MF PSS including CLF is able to reduce the low frequency oscillation and to achieve asymptotic tracking error between the reference mode state and the estimated plant state at different initial conditions.