• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.326-326
• /
• 2000

Continuous time system deadbeat controller(CdbC) has been studied mainly since 1992 especially by Japan researchers. They suggested delay elements. These elements stem from the finite Laplace Transform which is the starting point in deadbeat control system design in continuous time system. Every transfer function is established by these elements. From some conditions such as internal model stability and peasibility of a CdbC controller. unknown polynomials or coefficients can be calculated. In this paper, optimal pole placement of the closed loop system is suggested. From this. a CdbC controller with lower order can be obtained which attains the same level of weighted sensitivity function's H$_{\infty}$ norm used as a measure of the robustness property as existing CdbCs.

• Journal of Power Electronics
• /
• v.13 no.1
• /
• pp.122-138
• /
• 2013

Adaptive control of a peak current mode controlled (PCM) boost converter supplied by a PEM fuel cell is described in this paper. The adaptive controller with reference model and signal adaptation is developed in order to compensate the deviation of the response during the change of the operating point. The procedure for determining the adaptive algorithm's weighting coefficients, based on a combination of the pole-zero placement method and an optimization method is proposed. After applying the proposed procedure, the optimal adaptive algorithm's weighting coefficients can be determined in just a few iterations, without the use of a computer, thus greatly facilitating the application of the algorithm in real systems. Simulation and experimental results show that the dynamic behavior of a highly nonlinear control system with a fuel cell and a PCM boost converter, can fairly accurately be described by the dynamic behavior of the reference model, i.e., a linear system with constant parameters.

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

• Structural Engineering and Mechanics
• /
• v.78 no.3
• /
• pp.305-317
• /
• 2021

An AMD control system is usually built based on the original model of a target building. As a result, the fact leads a large calculation workload exists. Therefore, the orders of a structural model should be reduced appropriately. Among various model-reduction methods, a suitable reduced-order model is important to high-rise buildings. Meanwhile, a partial structural information is discarded directly in the model-reduction process, which leads to the accuracy reduction of its controller design. In this paper, an optimal technique is selected through comparing several common model-reduction methods. Then, considering the dynamic characteristics of a high-rise building, an improved balanced truncation (BT) method is proposed for establishing its reduced-order model. The abandoned structural information, including natural frequencies, damping ratios and modal information of the original model, is reconsidered. Based on the improved reduced-order model, a new reduced-order controller is designed by a regional pole-placement method. A high-rise building with an AMD system is regarded as an example, in which the energy distribution, the control effects and the control parameters are used as the indexes to analyze the performance of the improved reduced-order controller. To verify its effectiveness, the proposed methodology is also applied to a four-storey experimental frame. The results demonstrate that the new controller has a stable control performance and a relatively short calculation time, which provides good potential for structural vibration control of high-rise buildings.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.14 no.3
• /
• pp.68-76
• /
• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.