• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2000.10a
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• pp.79-83
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• 2000

A sliding mode fuzzy control (SMFC) with disturbance estimator is applied to design a controller for the third generation benchmark problem on an wind-excited building. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feed-back loop only. General structure of the SMFC is composed of a compensation part and a convergent part. The compensation part prevents the system diverge, and the convergent part makes the system converge to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feed-back loop and a feed-forward loop. To realize the virtual feed-forward loop for the wind-induced vibration control, disturbance estimation filter is introduced. the structure of the filter is constructed based on an auto regressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For the verification of the proposed algorithm, a numerical simulation is carried out on the benchmark problem of a wind-excited building. The results indicate that the present control algorithm is very efficient for reducing the wind-induced vibration and that the performance indices improve as the filter for wind force estimation is employed.

• Journal of Navigation and Port Research
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• v.33 no.6
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• pp.387-393
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• 2009

In this paper, a 3-D simulator was developed to estimate visually the performance of propelling and integrated control system of the underwater cleaning robot. Based on the dynamics analysis of the UCR, the 3-D model of the UCR was used in the simulator in which position and velocity are included Also, an input and control system using a joystick was developed, and the simulator was applied to the input and control of the simulator. Moreover, an integrated navigation control system was designed, and its performance was validated by a way-point simulator including a PI-based fuzzy control law.

• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.190-196
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• 2020

The step to obtain a process dynamic model through process experiments is very important because it needs times and expenditures. Step response method is one of the standard methods to have long been used for understanding process dynamics, obtaining dynamical models and designing control systems. For the step response, it is usually required to measure process output for a step input change in the open-loop manner. Its disadvantage criticized is the long open-loop operation. For this, a method based on the time-optimal control technique to minimize the test time for obtaining the step response has been recently presented. However, the method requires iterative computations for the minimization of test times. Here, a method where iterative computations are not required is proposed. Simulation results are presented to show that test times to obtain step responses are reduced considerably and an autotuning method based on the proposed method is compared with the relay feedback autotuning method accepted widely for the autotuning of controllers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• 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, ${\pi}$].

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.735-737
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• 2017

An Off grid or remote solar electric systems are an energy supply to our home or to our companies without the utility of Grid at all. Off grid solar systems are very important for those who live in remote locations especially for developing countries where getting the electric grid is extremely expensive, inconvenient or for those who doesn't need to pay a monthly bill with the electric bill in general. The main critical components of any solar power system or renewable energy harvesting systems are the energy storage systems and its charge controller system. Energy storage systems are the essential integral part of a solar energy harvesting system and in general for all renewable energy harvesting systems. To provide an optimal solution of both high power density and high energy density at the same time we have to use hybrid energy storage systems (HESS), that combine two or more energy storage technologies with complementary characteristics. In this present work, design and simulation we use two storage systems supercapacitor for high power density and lithium based battery for high energy density. Here the system incorporates fast-response supercapacitors to provide power to manage solar smoothing and uses a battery for load shifting. On this paper discuss that the total energy throughout of the battery is much reduced and the typical thermal stresses caused by high discharge rate responses are mitigated by integrating supercapacitors with the battery storage system. In addition of the above discussion the off grid solar electric energy harvesting presented in this research paper includes battery and supercapacitor management system, MPPT (maximum power point tracking) system and back/boost convertors. On this present work the entire model of off grid electric energy harvesting system and all other functional blocks of that system is implemented in MATLAB Simulink.

• Journal of Power Electronics
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• v.6 no.1
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• pp.52-66
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• 2006

This paper proposes a wind energy conversion system connected to a grid using a self-excited induction generator (SEIG) based on the maximum power point tracking (MPPT) control scheme. The induction generator (IG) is controlled by the MPPT below the base speed and the maximum energy can be captured from the wind turbine. Therefore, the stator currents of the IG are optimally controlled using the indirect field orientation control (IFOC) according to the generator speed in order to maximize the generated power from the wind turbine. The SEIG feeds a (CRPWM) converter which regulates the DC-link voltage at a constant value where the speed of the IG is varied. Based on the IG d-q axes dynamic model in the synchronous reference frame at field orientation, high-performance synchronous current controllers with satisfactory performance are designed and analyzed. Utilizing these current controllers and IFOC, a fast dynamic response and low current harmonic distortion are attained. The regulated DC-link voltage feeds a grid connected CRPWM inverter. By using the virtual flux orientation control and the synchronous frame current regulators for the grid connected CRPWM inverter, a fast current response, low harmonic distortion and unity power factor are achieved. The complete system has been simulated with different wind velocities. The simulation results are presented to illustrate the effectiveness of the proposed MPPT control scheme for a wind energy system. In the simulation results, the d-q axes current controllers and DC-link voltage controller give prominent dynamic response in command tracking and load regulation characteristics.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.26-36
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• 2013

Purpose of this study is to develop virtual components and environment for developing a controller of an Active Air Suspension System in laboratory that slough off existing development environment using real vehicle test. This paper presents an air spring modeling and analysis of air suspension system for a commercial vehicle. Preferentially, It was performed vehicle test for pneumatic system and an air spring for characteristic analysis of system. Each component of an air spring suspension system was developed through emulations and modeling of system for pressure and height sensors in the basis on test results in SILS environment. Non-linear characteristics of air spring are accounted for using the measured data. Also, pressure and volume relations for vehicle hight control is considered. After performance verification of virtual model was performed, we developed virtual environment based on HILS for an Active Air Suspension System. We studied estimation and verification technology for control algorithm that developed.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.1
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• pp.65-73
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• 2007

This paper presents an on-line correction method of current measurement errors for a pure-integration-based flux estimation down to 1-Hz stator frequency. An observer-based approach is taken as one possible solution of eliminating the dc offset and the negative sequence component of unbalanced gains in the synchronous coordinate. At the same time, the positive sequence component estimation is performed by creating an error signal between a motor model reference and an estimated q-axis rotor flux established by a permanent magnet (PM) in the synchronous coordinate. The compensator utilizes a PI controller that controls the error signal to zero. The proposed technique further contains a residual error compensator to completely eliminate miscellaneous disturbances in the estimated flux. The developed algorithm has been implemented on a 1.1-kW permanent magnet synchronous motor (PMSM) drive to confirm the effectiveness of the proposed scheme.