• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.109-115
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• 2010

A main technology of opening and closing a sluice gate is accurate synchronous and position control for the two cylinders when they are moving with the sluice gate together over 10[m]. Since the supply flow and supply pressure of cylinders are not constant and a nonlinear friction force of the piston in cylinders exists, a difference will be made between the displacement of two cylinders. This difference causes the sluice gate to deform and abrade, and even it may be out of order. In order to solve this problem we design two kinds of fuzzy PI controllers. The former is for a position control of two cylinders, the latter is for their synchronous control. We show some simulation results compare the performance of fuzzy PI controller to the conventional PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.153-158
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• 2010

This paper showed the possibilities of performance improvement of Brain-Computer Interface (BCI) decreasing classification error rates of EEG signals by applying Variance-Considered Machine (VCM) which proposed in our previous study. BCI means controlling system such as computer by brain signals. There are many factors which affect performances of BCI. In this paper, we used suggested algorithm as a classification algorithm, the most important factor of the system, and showed the increased correct rates. For the experiments, we used data which are measured during imaginary movements of left hand and foot. The results indicated that superiority of VCM by comparing error rates of the VCM and SVM. We had shown excellence of VCM with theoretical results and simulation results. In this study, superiority of VCM is demonstrated by error rates of real data.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.451-456
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• 2009

In this paper, a virtual force is generated and fed back to the operator to make the teleoperation more reliable, which reflects the relationship between a slave robot and an uncertain remote environment as a form of an impedance. In general, for the teleoperation, the teleoperated mobile robot takes pictures of the remote environment and sends the visual information back to the operator over the Internet. Because of the limitations of communication bandwidth and narrow view-angles of camera, it is not possible to watch certain regions, for examples, the shadow and curved areas. To overcome this problem, a virtual force is generated according to both the distance between the obstacle and the robot and the approaching velocity of the obstacle w.r.t the collision vector based on the ultrasonic sensor data. This virtual force is transferred back to the master (two degrees of freedom joystick) over the Internet to enable a human operator to estimate the position of obstacle at the remote site. By holding this master, in spite of limited visual information, the operator can feel the spatial sense against the remote environment. It is demonstrated by experiments that this collision vector based haptic reflection improves the performance of teleoperated mobile robot significantly.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.355-362
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• 2009

In this paper, we present a framework for managing group behaviors in multi-agent swarm systems. The framework explores the benefits by dynamic associations with the proposed artificial potential functions to realize complex swarming behaviors. A key development is the introduction of a set of flocking by dynamic association (DA) algorithms that effectively deal with a host of swarming issues such as cooperation for fast migration to a target, flexible and agile formation, and inter-agent collision avoidance. In particular, the DA algorithms employ a so-called systematic singular association (SSA) rule for fast migration to a target and compact formation through inter-agent interaction. The resulting algorithms enjoy two important interrelated benefits. First, the SSA rule greatly reduces time-consuming for migration and satisfies low possibility that agents may be lost. Secondly, the SSA is advantageous for practical implementations, since it considers for agents even the case that a target is blocked by obstacles. Extensive simulation presents to illustrate the viability and effectiveness of the proposed framework.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.3-12
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• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.602-608
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• 2011

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs $x_i$, i=1~6, the hidden layer consists of two hidden units for hidden outputs $o_j$, j=1~2, and the output layer consists of two units for the outputs ${\tau}_k$, k=1~2. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels. The initial q value was set to [0, 5, ${\pi}$].

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.25-33
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• 2009

Recently, the TS fuzzy models that include the linear equations in the consequent part are widely used for time series forecasting, and the prediction performance of them is somewhat dependent on the characteristics of time series such as stationariness. Thus, a new prediction method is suggested in this paper which is especially effective to nonstationary time series prediction. First, data preprocessing is introduced to extract the patterns and regularities of time series well, and then multiple model TS fuzzy predictors are constructed. Next, an appropriate model is chosen for each input data by an adaptive model selection mechanism based on rough sets, and the prediction is going. Finally, the error compensation procedure is added to improve the performance by decreasing the prediction error. Computer simulations are performed on typical cases to verify the effectiveness of the proposed method. It may be very useful for the prediction of time series with uncertainty and/or nonstationariness because it handles and reflects better the characteristics of data.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.779-786
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• 2009

This paper deals with $H_{\infty}$ fuzzy control problem of discrete-time nonlinear Markovian jump systems with time delay. The Takgi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the Markovian jump fuzzy system with time delay. Stochastic Lyapunov function is dependent on the operation modes of the system. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller are given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficient of the proposed design methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.710-715
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• 2010

As wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. The wind speed has a huge impact on the dynamic response of wind turbine. For this purpose, many control algorithms are in need for a method to measure wind speed to increase performance. Unfortunately, no accurate measurement of the effective wind speed is online available from direct measurements, which means that it must be estimated in order to make such control methods applicable in practice. In this paper, a new method based on Kalman filter and artificial neural network is presented for the estimation of the effective wind speed. To verify the performance of the proposed scheme, some simulation studies are carried out.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.89-98
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• 2017

The control moment gyroscope(CMG) can be used for essential balancing control of a one-wheeled mobile robot. A single-gimbal CMG has a simple structure and can supply strong restoring torque against external disturbances. However, the CMG generates unwanted directional torque also besides the restoring torque; the unwanted directional torque causes instability in the one-wheeled robot control system that has high rotational degrees of freedom. This study proposes a control system for a one-wheeled mobile robot by using a CMG scissored pair to eliminate the unwanted directional torque. The well-known LQR control algorithm is designed for robustness against modeling error in the dynamic motion equations of a one-wheeled robot. Computer simulations for 3D nonlinear dynamic equations are carried out to verify the proposed control system with the CMG scissored pair and the LQR control algorithms.