• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.4
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• pp.165-174
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• 2000

This paper presents the application of H$\infty$ control synthesis using LMI optimization method to power system stabilizer(PSS) design. Since power system is usually operated under circumstance of unmeasurable uncertainties and external disturbances, the improvement of small signal stability becomes one of the most important issue for securing system stability and preventing low frequency oscillation phenomena. The LMI optimized H$\infty$ PSS provides robust performance and guarantees the internal stability under these operating conditions. The global optimal H$\infty$ norm is found using LMI convex optimization method which is more systematic than standard two Riccati solution method. The design results are simulated for a case study. We verified that the LMI method shows the best performance characteristic smong standard Riccati method and conventional lead/lag method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2464-2466
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• 2000

When linear PI controller is used in speed control of induction motor, there happen some weaks which is very difficult to find optimal control gain at time of changing speed and load. In this paper, Fuzzy system incorporated with PI controller is proposed in order to that defects. PI gain is calculated by theoretical basis and fuzzy control is translated human expert's knowledge and experiences into rules numerically. Also it modifies and compensates PI gains in realtime. As comparing the motor characteristics of proposed fuzzy-PI speed controller to PI speed controller of a Vector controlled induction motor system in the increasing load torque and speed change during start and stop, The simulation results show robust and good performance.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.3
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• pp.156-165
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• 2004

Concentrations of substrates, glucose, and ammionia in biological processes have been on-line monitored by using glucose-flow injection (FIA) and ammonia-FIA systems. Based on the on-line monitored data the concentrations of substrates have been controlled by an on-off controller, a PID controller, and a neural network (NN) based controller. A simulation program has been developed to test the control quality of each controller and to estimate the control parameters. The on-off controller often produced high oscillations at the set point due to its low robustness. The control quality of a PID controller could have been improved by a high analysis frequency and by a short residence time of sample in a FIA system. A NN-based controller with 3 layers has been developed, and a 3(input)-2(hidden)-1(output) network structure has been found to be optimal for the NN-based controller. The performance of the three controllers has been tested in a simulated process as well as in a cultivation process of Saccharomyces cerevisiae, and the performance has also been compared to simulation results. The NN-based controller with the 3-2-1 network structure was robust and stable against some disturbances, such as a sudden injection of distilled water into a biological process.

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.621-642
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• 2011

Passive tuned mass dampers (TMDs) efficiently suppress vibrations induced by quasi-stationary dynamic inputs, such as winds, sea waves or traffic loads, but may prove of little use against pulse-like excitations, such as near-field (NF) ground motions. The extent of such impairment is however controversial, partly due to the different evaluation criteria adopted within the literature, partly to the limited number of seismic records used in most investigations. In this study, three classical techniques and two new variants for designing a TMD on an SDOF structure are tested under 338 NF records from the PEER NGA database, including 156 records with forward-directivity features. Percentile response reduction spectra are introduced to statistically assess TMD performance, and TMD robustness is verified through Monte Carlo simulations. The methodology is extended to a variety of MDOF bending-type and shear-type frames, and simulated on a case study building structure recently constructed in Central Italy.Results offer an interesting insight into the performance of TMDs against NF earthquakes, ultimately showing that, if properly designed and sufficiently massive, TMDs are effective and robust even in the face of pulse-like ground motions. The two newly proposed design techniques are shown to generally outperform the classical ones.

• Structural Engineering and Mechanics
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• v.41 no.1
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• pp.25-41
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• 2012

Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a scheme for crack identification based on a Kriging surrogate model is proposed. A modified rectangular grid (MRG) is introduced to move some sample points lying on the boundary into the internal design region, which will provide more useful information for the construction of Kriging model. The initial Kriging model is then constructed by samples of varying crack parameters (locations and sizes) and their corresponding modal frequencies. For identifying crack parameters, a robust stochastic particle swarm optimization (SPSO) algorithm is used to find the global optimal solution beyond the constructed Kriging model. To improve the accuracy of surrogate model, the finite element (FE) analysis soft ANSYS is employed to deal with the re-meshing problem during surrogate model updating. Specially, a simple method for crack number identification is proposed by finding the maximum probability factor. Finally, numerical simulations and experimental research are performed to assess the effectiveness and noise immunity of this proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.66-72
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• 2000

As the demand for the design of modular manipulators or special purpose manipulators has increased, task based design to design an optimal manipulator for a given task become more and more important. However, the complexity with a large number of design parameters, and highly nonlinear and implicit functions are characteristics of a general manipulator design. To achieve the goal of task based design, it is necessary to develop a methodology to solve the complexity. This paper addresses how to determine the kinematic parameters of a two-degrees of freedom manipulator with parallelogram five-bar link mechanism from a given task, namely, how to map a given task into the kinematic parameters. With simplified example of designing a manipulator with five-bar link mechanism, the methodology for task based design is presented. And it introduces formulations of a given task and manipulator specifications, and presents a new dexterity measure for manipulator design. Also the optimization problem with constraints is solved by using a genetic algorithm that provides robust search in complex spaces.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.18-27
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• 2002

This paper presents an implementation of digital high-performance speed sensorless control system of an induction motor drives with Direct Torque Control(DTC). The system consists of closed loop stator flux and torque observer, speed and torque estimators, two hysteresis controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP controller board. The stator flux observer is based on the combined current and voltage model with stator flux feedback adaptive control for wide speed range. The speed estimator is using the model reference adaptive system(MRAS) with rotor flux linkages for speed turning signal estimation. In order to prove the suggested speed sensorless control algorithm, and to obtain a high-dynamic robust adaptive performance, we have some simulations and actual experiments at low(20rpm) and high(1000rpm) speed areas. The developed speed sensorless system are shown a good speed control response characteristic, and high performance features using 2.2[kW] general purposed induction motor.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.1-9
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• 2002

Among the state-space description of discrete vent systems, the max-plus algebra is known as one of the effective approach. This paper proposes a model predictive control (MPC) design method based on the max-plus algebra. Several studies related to these topics have been done so far under the constraints that system parameters are constant. However, in practical systems such as production systems, it is common and sometimes inevitable that system parameters vary by each event. Therefore, it is of worth to design a new MPC controller taking account of adjustable system parameters. In this paper, we formulate system parameters as adjustable ones, and they are solved by a linear programing method. Since MPC determines optimal control input considering future reference signals, the controller can be more robust and the operation cost can be reduced. Finally, the proposed method is applied to a production system with three machines, and the effectiveness of the proposed method is verified through a numerical simulation.

• Journal of Power Electronics
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• v.11 no.5
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• pp.734-742
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• 2011

In this paper a robust method is presented for the combined design of STATCOM and Power System Stabilizer (PSS) controllers in order to enhance the damping of the low frequency oscillations in power systems. The combined design problems among PSS and STATCOM internal ac and dc voltage controllers has been taken into consideration. The equations that describe the proposed system have been linearized and a Fuzzy Logic Controller (FLC) has been designed for the PSS. Then, the Particle Swarm Optimization technique (PSO) which has a strong ability to find the most optimistic results is employed to search for the optimal STATCOM controller parameters. The proposed controllers are evaluated on a single machine infinite bus power system with the STATCOM installed in the midpoint of the transmission line. The results analysis reveals that the combined design has an excellent capability in damping a power system's low frequency oscillations, and that it greatly enhances the dynamic stability of power systems. Moreover, a system performance analysis under different operating conditions and some performance indices studies show the effectiveness of the combined design.