• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.4
• /
• pp.380-388
• /
• 2006

A noisy behavior of the time domain passivity controller during the period of low velocity is analyzed. Main reasons of the noisy behavior are investigated through a simulation with a one-DOF (Degree of Freedom) haptic interface model. It is shown that the PO/PC is ineffective in dissipating the produced energy when the sign of the velocity, which is numerically calculated from the measured position, is suddenly changed, and when this velocity is zero. These cases happen during the period of low velocity due to the limited resolution of the position sensor. New methods, ignoring the produced energy from the velocity sign change, and holding the control force while the velocity is zero, are proposed for removing the noisy behavior. The feasibility of the developed methods is proved with both a simulation and a real experiment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.4
• /
• pp.855-859
• /
• 2012

This study derives a generalized PSD formula in the LTV phase noise theory for noisy oscillators. The derived formula analytically proves that the LTV phase noise theory can predict the conservation of the power in the noisy oscillation signals. Additionally, the derived formula allows the theory to account for the behavior of the power spectrum over the entire frequency range including the regions around higher harmonics as well as fundamental frequency.

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.2
• /
• pp.42-53
• /
• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of the Korean Home Economics Association
• /
• v.27 no.1
• /
• pp.85-96
• /
• 1989

The purpose of study was to survey the indoor noise of apartment houses, residents, attitudes and their adaptation behavior in order to offer the information helpful to apartment designers and residents, in their housing policy. Documentary research and questionnaire survey methods were used in this research. The sample was taken from 187 housewives living in apartments in Seoul. Data were analyzed with the SPSS program. The results were as follow : 1. It was found that apartment residents pointed out washing machine noise inside the home, piano and other musical instruments noise outside the home. 2. Piano and other musical instrument noise were heard at 3 to 6 pp.m. when residents heard the noise, and water supply and drainage noise in bathrooms were found most noisy. 3. Apartment residents were discontent with noise outside the home, and they displayed positive adaptation behavior at a reduced noise level. 4. Attitudes arising from indoor noise in apartment houses and human noise, water supply and drainage noise, doorway opening and closing noise were found to be significant in sampled apartment groups. 5. The youngest child's age was a significant variable on the residents' attitudes and adaptation behavior of indoor noise in apartment houses. 6. Between the resident' attitudes and adaptation behavior involving indoor noise in apartment houses. 6. Between the resident' attitueds and adaptation behavior involving indoor noise apartment houses, the more they became discontented, the more quickly they adapted in a postive manner.

• Communications for Statistical Applications and Methods
• /
• v.4 no.2
• /
• pp.453-463
• /
• 1997

Nonparametric kernel regression has recently gained widespread acceptance as an attractive method for the nonparametric estimation of the mean function from noisy regression data. Also, the practical implementation of kernel method is enhanced by the availability of reliable rule for automatic selection of the bandwidth. In this article, we propose a method for automatic selection of the bandwidth that minimizes the asymptotic mean square error. Then, the estimated bandwidth by the proposed method is compared with the theoretical optimal bandwidth and a bandwidth by plug-in method. Simulation study is performed and shows satisfactory behavior of the proposed method.

• Journal of the Korea Society for Simulation
• /
• v.28 no.4
• /
• pp.21-32
• /
• 2019

Inspired by the social behavior models of a bird flock or fish school, particle swarm optimization (PSO) is a popular metaheuristic optimization algorithm and has been widely used from solving a complex optimization problem to learning a artificial neural network. However, PSO is difficult to apply to many real-life optimization problems involving stochastic noise, since it is originated in a deterministic environment. To resolve this problem, this paper incorporates a resampling method called the uncertainty evaluation (UE) method into PSO. The UE method allows the particles to converge on the accurate optimal solution quickly in a noisy environment by selecting the particles' global best position correctly, one of the significant factors in the performance of PSO. The results of comparative experiments on several benchmark problems demonstrated the improved performance of the propose algorithm compared to the existing studies. In addition, the results of the case study emphasize the necessity of this work. The proposed algorithm is expected to be effectively applied to optimize complex systems through digital twins in the fourth industrial revolution.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.624-636
• /
• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.2 s.233
• /
• pp.277-283
• /
• 2005

Kriging model is widely used as design analysis and computer experiment (DACE) model in the field of engineering design to accomplish computationally feasible design optimization. In general, kriging model has been applied to many engineering applications as an interpolation model because it is usually constructed from deterministic simulation responses. However, when the responses include not only global nonlinearity but also numerical error, it is not suitable to use Kriging model that can distort global behavior. In this research, generalized kriging model that can represent both interpolation and regression is proposed. The performances of generalized kriging model are compared with those of interpolating kriging model for numerical function with error of normal distribution type and trigonometric function type. As an application of the proposed approach, the response of a simple dynamic model with numerical integration error is predicted based on sampling data. It is verified that the generalized kriging model can predict a noisy response without distortion of its global behavior. In addition, the influences of maximum likelihood estimation to prediction performance are discussed for the dynamic model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.638-642
• /
• 2001

In this paper we propose a noise reduction algorithm which based on cellular automata with the local median rule. It is supposed that there is no information about the features of the image that must be improved. The proposed method behavior is to locally increase or decrease the gray level differences of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. We have found that the automata present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuss the advantage and efficiency.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.2
• /
• pp.343-348
• /
• 2001

In this paper we propose a noise reduction algorithm which based on cellular automata with the local median rule. It is supposed that there is no information about the features of the image that must be improved. The proposed method behavior is to locally increase or decrease the gray level differences of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. We have found that the automata present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuss the advantage and efficiency.