• 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 Korea Society of Computer and Information
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• v.16 no.8
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• pp.57-66
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• 2011

In this paper, it is proposed for algorithm to detect human efficiently using a edge symmetry and gradient directional characteristics in realtime by the feature extraction in a single input image. Proposed algorithm is composed of three stages, preprocessing, region partition of human candidates, verification of candidate regions. Here, preprocessing stage is strong the image regardless of the intensity and brightness of surrounding environment, also detects a contour with characteristics of human as considering the shape features size and the condition of human for characteristic of human. And stage for region partition of human candidates has separated the region with edge symmetry for human and size in the detected contour, also divided 1st candidates region with applying the adaboost algorithm. Finally, the candidate region verification stage makes excellent the performance for the false detection by verifying the candidate region using feature vector of a gradient for divided local area and classifier. The results of the simulations, which is applying the proposed algorithm, the processing speed of the proposed algorithms is improved approximately 1.7 times, also, the FNR(False Negative Rate) is confirmed to be better 3% than the conventional algorithm which is a single structure algorithm.

• Journal of the Korea institute for structural maintenance and inspection
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• v.9 no.1
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• pp.197-204
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• 2005

Multipurpose Floor Level Joint(MFLJ) is a new construction technology system which was developed in domestic. By using this system, it is possible not only to absorb the deformation at expansion joint due to shrinkages of concrete but also to make ease the floor leveling during the concrete casting at floor. The system consists of two elements, supporting devices and rails. Their structural capacities were verified through several experimental programs, such as compressive strength test of support and bending test of rail. The purpose of this paper is to evaluate the deformation absorbing capacity of the floor level joint. An experimental work was carried out to simulate the deformation condition at the joint and the test result was analyzed and evaluated. In addition, FEM analysis for expansion joint of typical building was also performed to predict the real behavior of MFLJ. The test results showed that MFLJ has sufficient deformation capacity required to act as expansion joint.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.102-109
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• 2014

In this paper, an algorithm to design fuzzy PID controllers is proposed. The proposed controllers are composed of fuzzy rules of which consequences are linear PID controllers and are designed with help of TSK fuzzy controllers. TSK fuzzy controllers are designed from TSK fuzzy model using pole assignment and have outstanding ability making the output response of nonlinear systems similar to the desired one. However, because of its structure complexity the TSK fuzzy controller is difficult to be used in industry. The proposed controllers have PID controller structure which can be easily realized, and are designed by using the data obtained from control simulations with TSK fuzzy controllers. To verify the proposed algorithm, two example simulations are performed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.6
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• pp.77-82
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• 2005

This paper is proposed fuzzy neural network(FNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.21-26
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• 2007

Output voltage waves of a DC/AC inverter system are likely to be distorted if variable loads e.g. motors or rectifiers exist in the output terminal. This paper designs a disturbance observer-based PI-controller for a single-phase inverter system that is robust against load changes. In this Paper, we regard the output voltage changes due to various loads as disturbances of the control system. Then we design a disturbance observer for estimation of the disturbances caused by the load current and any other error sources (such as parameter uncertainties and model mismatches etc.). In order to test the performance of the proposed control law, simulation studies are carried out for a single-phase inverter system using SimPowerSystem of Matlab Simuink. Compared to a simple PI-control, the disturbance observer-based controller shows enhanced performance in transient responses for step load changes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2054-2061
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• 2015

Biologically inspired modeling techniques have received considerable attention for their robustness, scalability, and adaptability with simple local interactions and limited information. Among these modeling techniques, Gene Regulatory Networks (GRNs) play a central role in understanding natural evolution and the development of biological organisms from cells. In this paper, we apply GRN principles to the WSN system and propose a new GRN model for decentralized node scheduling design to achieve energy balancing while meeting delay requirements. Through this scheme, each sensor node schedules its state autonomously in response to gene expression and protein concentration, which are controlled by the proposed GRN-inspired node scheduling model. Simulation results indicate that the proposed scheme achieves superior performance with energy balancing as well as desirable delay compared with other well-known schemes.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.347-356
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• 2017

It is well-known that the face recognition method via sparse representation has been proved very robust and showed good performance. Its weakness is, however, that its time complexity is very high because it should solve $L_1$-minimization problem to find the sparse solution. In this paper, we propose to use the ROMP(Regularized Orthogonal Matching Pursuit) method for the sparse solution, which solves the $L_2$-minimization problem with regularization condition using the greed strategy. In experiments, we shows that the proposed method is comparable to the existing best $L_1$-minimization solver, Homotopy, but is 60 times faster than Homotopy. Also, we proposed C-SCI method for classification. The C-SCI method is very effective since it considers the sparse solution only without reconstructing the test data. It is shown that the C-SCI method is comparable to, but is 5 times faster than the existing best classification method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.24-32
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• 2010

In this paper we proposed an object tracking system that detects the abandoned and removed objects, which is to be used in the intelligent surveillance applications. After the GMM based background subtraction and by using histogram method, the static region is identified to detect abandoned and removed objects. Since the system is implemented on DSP chip, it operates in realtime and is programmable. The input videos used in the experiment contain various indoor and outdoor scenes, and they are categorized into three different complexities; low, midium and high. By 10 times of experiment, we obtained high detection ratio at low and medium complexity sequences. On the high complexity video, successful detection ratio was relatively low because the scene contains crowdedness and repeated occlusion. In the future work, these complicated situation should be solved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.11
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• pp.1185-1191
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• 2014

An integrated ship area network has functionality of remote control and autonomous management of various sensors and instruments embedded or boarded in a ship. For such environment, a wireless bridge is essential to transmit control and/or managing information to sensors or instruments from a central integrated ship area network station. In this paper, one of reliable schemes of In-ship sensor networks using a Grid-based WPAN is proposed. The proposed scheme is based on a novel grid network which allows a multi-path communication, and is robust, energy efficient. The results demonstrate that the proposed Grid-based WPAN outperforms the IEEE 802.15.4 based network in terms of success ratio and power efficiency.