• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1195-1199
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• 1998

In this paper a design method of robust power system stabilizers is proposed by means of robust linear quadratic regulator design technique under power system's operating condition change, which is caused by inner structure uncertainties and disturbances into a power system. It is assumed that the uncertainties present in the system are modeled as one equivalent signal. In this connections an optimal LQR control input for disturbance rejection, the output feedback gain for eliminating the disturbance are calculated. In this case. PSS input signal is obtained on the basis of weighted ${\Delta}P_e$ and $\Delta\omega$. In order to stabilize the overall control of system. Pole placement algorithm is applied in addition. making the poles of the closed loop system to move into a stable region in the complex plane. Some simulations have been conducted to verify the feasibility of the proposed control method on a machine to infinite bus power system. From the simulation results validation of the proposed method could be achieved by comparisons with the conventional PSS with phase lag-lead compensation.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.351-370
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• 2022

The design of mechanical structures aims to meet criteria, together with the safety of operators and lives in the vicinity of the equipment. Thus, there are several cases that meeting the desired specification causes the mechanical device to perform unstable and, sometimes, chaotic behavior. In these cases, control methods are applied in order to stabilize the device when in operation, aiming at the physical integrity of the component and the device operators. In this work, we will develop a study about the influence of a controller applied in a non-ideal capsule system operating with uncertain parameters, being non-existent in the literature. For this, two initial conditions were used: one that the capsule starts from rest and another that it is already in motion. Thus, the effectiveness of the controller can be assessed in both initial conditions, restricting the movement of the internal vibration-impact system to the capsule.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.390-393
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• 2007

In this paper, applications of self recurrent neuro-fuzzy controller to stabilization of nonlinear system are considered. The architecture of self recurrent neuro-fuzzy controller is fix layer, and the hidden layer is comprised of self recurrent architecture. Also, generalized dynamic error-backpropagation algorithm is used for the learning of the self recurrent neuro-fuzzy controller. To demonstrate the efficiency of the self recurrent neuro-fuzzy control algorithm presented in this study, a self recurrent neuro-fuzzy controller was designed and then a comparative analysis was made with LQR controller through an simulation.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.72-78
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• 2012

In this research an equilibrium point of a Wheeled Inverted Pendulum (WIP) running on an inclined road is derived and validated by some experiments. Generally, The WIP has stable and unstable equilibrium point. Only unstable equilibrium point is interested in the research. To keep the WIP on the unstable equilibrium point, the WIP is consistently controlled. A controller for the WIP needs a reference state for the equilibrium point. The reference state can be obtained by studying an equilibrium point of the WIP. This research is deriving dynamic equations of the WIP running on the inclined road and equilibrium of it based on statics. Several experiments are carried out to show the validation of the equilibrium point.

• Structural Engineering and Mechanics
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• v.49 no.3
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• pp.329-353
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• 2014

Increasing usage of tank cars and their intrinsic instability due to sloshing of contents have caused growing maintenance costs as well as more frequent hazards and defects like derailment and fatigue of bogies and axels. Therefore, varieties of passive solutions have been represented to improve dynamical parameters. In this task, assuming 22 degrees of freedom, dynamic analysis of partially filled tank car traveling on a curved track is investigated. In order to consider stochastic geometry of track; irregularities have been derived randomly by Mont Carlo method. More over the fluid tank model with 1 degree of freedom is also presented by equivalent mechanical approach in terms of pendulum. An active suspension system for described car is designed by using linear quadratic optimal control theory to decrease destructive effects of fluid sloshing. Eventually, the performance of the active suspension system has been compared with that of the passive one and a study is carried out on how active suspension may affect the dynamical parameters such as displacements and Nadal's derailment index.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.139.3-139
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• 2001

The free-model concept is introduced as an alternative intelligent system technique to design a controller with input and output data only. The idea of free model comes from the Taylor series approximation, where an output can be estimated when such data as position, velocity, and acceleration are known. The parameters in the free model can be estimated using the input-output data and a controller can be designed based on the free model. The free model thus developed is shown to be controllable, observable, and robust. The accuracy of the free-model approximation can be improved by increasing the observation window and the order of the free model. The LQR method is applied to the free model to design power system stabilizers ...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.384-388
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• 1996

The closed-loop system modeling of an Active/semiactive suspension system has been accomplished through an artificial neural Networks. The 7DOF full model as the system equation of motion has been derived and the output feedback linear quadratic regulator has been designed for the control purpose. For the neural networks training set of a sample data has been obtained through the computer simulation. A 7DOF full model with LQR controller simulated under the several road conditions such as sinusoidal bumps and the rectangular bumps. A general multilayer perceptron neural network is used for the dynamic modeling and the target outputs are feedback to the input layer. The Backpropagation method is used as the training algorithm. The modeling of system and the model validation have been shown through computer simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.93-101
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• 1993

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.382-389
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• 2006

구조 재료와 시공기술의 발달로 구조물은 높고 길게 설계할 수 있게 되었으나, 그에 따른 진동 문제와 사용성에 관한 문제가 발생하였고 구조물의 과다한 변위는 구조물에 심각한 손상을 발생 시켰다. 이러한 구조물의 진동 문제를 해결하기 위하여 본 논문에서는 확률신경망이론을 사용한 구조물의 능동제어방법을 제안하였다. 구조물의 제어를 위하여 LQR 제어알고리즘을 이용하여 구조물의 상태벡터와 제어력을 구한 후, 상태벡터를 입력으로 제어력을 출력으로 하는 확률신경망의 훈련패턴을 구성하였다. 제안된 방법을 사용하여 지진하중을 받는 3층 빌딩구조물을 제어하였고, 기존의 인공신경망의 제어 결과와 비교하였다.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.161-169
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• 2007

The PLL equivalent augmented system incorporated with state feedback is proposed in this paper. The optimal value of filter time constant of loop filter in the phase-locked loop control system and the optimal state feedback gain designed by using linear quadratic regulator approach are derived. This approach allows the PLL control system to employ the large value of the phase-frequency gain $K_d$ and voltage control oscillator gain $K_o$. In designing, the structure of phase-locked loop control system will be rearranged to be a phase-locked loop equivalent augmented system by including the structure of loop filter into the process and by considering the voltage control oscillator as an additional integrator. The designed controller consisting of state feedback gain matrix K and integral gain $k_1$ is an optimal controller. The integral gain $k_1$ related to weighting matrices q and R will be an optimal value for assigning the filter time constant of loop filter. The experimental results in controlling the second-order lag pressure process using two types of loop filters show that the system response is fast without steady-state error, the output disturbance effect rejection is fast and the tracking to step changes is good.