This paper proposes an efficient method of hydro-thermal scheduling in coordination with head variation and hydraulically coupled plants using Evolutionary Programing(EP). Based on the EP technique, the proposed algorithm is capable of determining the global optimal solutions. The constraints such a power balance condition, water available condition and transmission losses are embedded and satisfied throughout the proposed EP approach. The effectiveness of the proposed approach is demonstrated on the test systems and compared to those of other method. The results show that the new approach obtains a more highly optimal solutions than the conventional other methods such as newton-raphson method, Dynamic Programming(DP), LU factorization.

Most conventional protection relays are based on processing information in the spectrum that is close to or at power frequency. It is, however, widely known that faults on transmission lines produce frequency components of a wide range. High frequency signals caused by sudden changes in system voltage that occurs in the immediate post-fault period are generally outside the bandwidth of receptibility of most protection scheme. In this respect, a specially designed stack tuner is connected to the coupling capacitor of CVT, in order to capture the high frequency signals. Digital signal processing is then applied to the captured information to determine whether the fault is inside or outside the protected zone, and to discriminate the fault type. In this paper, modal transform is not applied to fault generated signals, because signals which are converted by modal transform are not have an information of each phase any longer. Instead, using peak voltage value of data windows is able to discriminate fault type. The paper concludes by presenting fault detection and discrimination of various faults on transmission line which are based on extensive simulation studies carried out on a typical 154kV Korean transmission line, using the EMTP software.

This paper discusses the development of an interactive and graphic software for the education and training of power system operation and control, especially for students and beginners. This software has a lot of functions for users to simulate the power system operation and control with ease. These functions included in this software are followings. First, this software includes a Graphic User Interface (GUI) - which contains interactive simulation scheme, Windows dialog box, graphic representations, and graphic icons - so that users can handle the software in user-friendly environments. Second, it uses a graphic editor so that users can easily edit the one-line diagram of the power system. Third, it prepares a database system so that users can manage the power system data for simulation easily. Fourth, the application modules included in the software are the Economic Dispatch (ED) and the Automatic Load-Frequency Control (ALFC). These application modules are designed as independent modules. Using the ED module, users can understand the basic concepts of the ED with ease. And using the ALFC module, they can easily acquire the basic understanding of the response of the ALFC between the two-area systems. The proposed software is tested on both the 16 bus and the two-area sample system. The test has confirmed the functions of the developed software. It is anticipated that the software will be useful for the education and training of power system operation and control for the power engineering study at university or for the training of the beginner at power industry.

This paper presents a DSM monitoring methodology that is able to evaluate the impact of DSM programs especially focused on the strategic conservation i.e. the enhancement of end-use energy efficiency. For an effective assessment of DSM programs, it is foremost necessary to examine the market characteristics on the specific end-use appliance according to the customer's adoption of DSM programs. The proposed monitoring methodology contains a diffusion process of high efficient end-uses considering major factors of DSM impact such as, price, reference capacity, forecasted capacity and lifetime of end-use appliances. Case studies show the projection of power reductions and energy savings resulted from DSM monitoring in order to diagnose the current status properly and provide a baseline of DSM policy and analysis.

The saddle node bifurcation (SNB) and the distance voltage instability are valuable information in power system planning and operation. This paper presents a new efficient, robust and unified strategy to compute the SNB by the combined use of the continuation power flow (CPF), Point of Collapse (PoC) method, and the method of a pair of multiple load flow solutions (PMLFS) with Lagrange interpolation utilizing only their advantages: the approximate nose curves and critical loading are determined fast by Lagrange-interpolating two stable and two unstable solutions obtained by using the robust CPF and PMLFS; the exact SNB is computed by the quadratically converging PoC method. The proposed method has been tested on Klos-Kerner 11-bus, New England 30-bus, IEEE 118-bus and KEPCO 791-bus systems. The method is found to be so efficient that computation time for determining the SNB of the KEPCO 791-bus system is 17.82 sec by a notebook PC with 300 MHz Pentium processor.

The distance in load parameter space to the closest saddle node bifurcation (CSNB) point provides the worst case power margin to voltage instability and the left eigenvector at CSNB identifies the most effective direction to steer the system to maximize voltage stability under contingency. This paper presents an improved direct method for computing CSNB: the order of nonlinear systems equations is reduced to about twice of the size of load flow equations in contrast to about three-times in Dobson's direct method; the initial guess for the direct method is computed efficiently and robustly by combined use of continuation power flow, a pair of multiple load flow solution with Lagrange interpolation. It is also shown that voltage stability may be enhanced significantly with shift of generations in the direction of the left eigenvector at CSNB.

This paper presented to design the power system stabilizer(PSS) for a turbo-generator system using LQG/LTR control synthesis for improving small-signal stability. Application study of LGG/LTR control synthesis is more appropriate in this system since a turbo-generator system is usually operated under circumstance of unmeasurable uncertainties and external disturbance. The LQG/LTR control theory was briefly reviewed for good understanding and the reasonable design approach. The design results are simulated for a case study and to check the system performance in comparison with currently operating lead-lag filtered PSS performance.

QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The fundamental concept of QFT is a loop shaping procedure that a suitable controller can be found by shaping a nominal loop transfer function. The loop shaping synthesis involves the identification of a structure and the specialization of parameter optimization of a desired system. This paper presents an improved loop shaping approach of QFT with model validation using GA(Genetic Algorithm). The method presented in this paper removes the problems of iterative operation, transformation error, and model validation in the conventional methods without consideration of frequency domain.

In this paper, the optimal controller which decouples a coupled multivariable system and minimizes a quadratic performance index is proposed. Design of the controller is based on the two-degree-of-freedom standard model. The class of all stabilizing and decoupling controllers is parametrized first and the $H^{2}$optimal controller is obtained by using this parametrized form. An illustrative example for a $2{\times}2$ plant is given.

A new robust controller design methodology for single-input single-output systems is proposed, where the proposed controller consists of a conventional or optimal servo controller at the outer loop as well as the robust internal-loop compensator(RIC) to eliminate the model uncertainty and external disturbance. It is shown that RIC with finite gain can make actual systems be nominal models within a prespecified error bound. And, it is also shown that RIC-based system is robustly stable regardless of input saturation. Several numerical examples are illustrated to show validities of the proposed robust controller.

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

This paper considers the transient stability problem of power system. The power system model is given as interconnected system consisting of many machines which are described by swing equations. We design a transient stability controller using passivity and neural network. The structure of the neural network controller is derived using a filtered error/passivity approach. In general, a neural network cannot be guaranteed to be passive, but the weight tuning algorithm given here do guarantee desirable passivity properties of the neural network and hence of the closed-loop error system. Moreover proposed controller shows good robustness by simulation for uncertainties in parameters, which can not be shown in the speed gradient method proposed by Fradkov[3,7].

PID controllers with constant gains have been widely used in various control systems. But it is difficult to have uniformly good control performance in all operating conditions. In this paper, we propose a variable PID controller for robot manipulators. We divide total workspace of manipulators into several subspaces. PID controllers in each subspace are optimized using evolution strategy which is a kind of global search algorithm. In real operation, the desired trajectories may cross several subspaces and we select the corresponding gains in each subspace. The gains may have large difference on the boundary of subspaces, which may cause oscillatory motion. So we use artificial neural network to have continuous smooth gain curves to reduce the oscillatory motion. From the experimental results, although the proposed variable PID controller for robots should pay for some computational burden, we have found that the controller is more superior to the conventional constant gain PID controller.

This paper is concerned with the balancing motion formulation and the control of ZMP (zero moment point) for a biped walking robot with balancing joints. The balancing equation of a biped robot can be modeled as the second order non-homogeneous differential equation, which makes it possible to plan the desired trajectories for various gaits or motions. Also, the balancing motion can be defined easily by solving the differential equation without pre-processing or heuristic procedures. The actual experiments are performed on biped walking robot system IWR-III, developed in our Automatic Control Lab. The system has the structure of three pitches in each leg, and one roll and one prismatic type in balancing joints. The walking simulations and the experimental results on IWR-III are shown using the proposed formula and control algorithm.

A Hierarchical vector Quantization scheme is implemented and an optimal thresholding technique of quadtree segmentation for performing high quality low bit rate image compression is proposes. A mathematical model is constructed under the assumption that the standard deviations of sub-blocks are larger than or equal to the standard deviation of the upper level block which is generated by merging of sub-blocks. This thresholding technique based on the mathematical modeling allows producing about 1 dB improved performance in terms of PSNR at most ranges of bit rates over the quadtree coder, which is based on MSE for quadtree segmentation.

We propose two new classes of robust blind equalization algorithms against abrupt changes of channel conditions, which we call a triple-mode algorithm(TMA) and an automatic switch-over algorithm(ASA). The conventional DMGSA exhibits slow convergence rates due to the incorrect equalizer tap-updating process under the severe channel conditions. In order to speed up the convergence process, the TMA operates in triple-mode that is based on the dual-mode of the DMGSA incorporated with the tap-updating control modes of the SGA as well as the MSGA. Without resorting to the decision region for selecting the operation mode in the TMA, the ASA automatically switches the blind mode to the smoother conventional decision-directed mode. The ASA uses the error functional that is the weighted sum of the Generalized Sato error and the decision-directed error, where the weights correspond to the channel conditions. Test results on 16-QAM and 8-VSB datas confirm that the TMA and the ASA perform well under the sudden changes of channel conditions.

The musculotendon model is presented to show the declines in muscle force and shortening velocity during muscle fatigue due to the repeated functional electrical stimulation (FES). It consists of the nonlinear activation and contraction dynamics including physiological concepts of muscle fatigue. The activation dynamics represents $Ca^{2+}$ binding and unbinding mechanism with troponins of cross-bridges in sarcoplasm. It has the constant binding rate or activation time constant and two step nonlinear unbinding rate or inactivation time constant. The contraction dynamics is the modified Hill type model to represent muscle force - length and muscle force - velocity relations. A muscle fatigue profile as a function of the intracellular acidification, pH is applied into the contraction dynamics to represent the force decline. The computer simulation shows that muscle force and shortening velocity decline in stimulation time. And we validate the model. The model can predicts the proper muscle force without changing its parameters even when existing the estimation errors of the optimal fiber length. The change in the estimate of the optimal fiber length has an effect only on muscle time constant in transient period not on the tetanic force in the steady-state and relaxation periods.