• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.638-643
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• 2012

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

• Journal of Ocean Engineering and Technology
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• v.32 no.6
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• pp.440-446
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• 2018

The effects of an anti-rolling tank (ART) on vessel motions were numerically investigated. The potential-based BEM vessel motion simulation program and particle-based computational fluid dynamics program were dynamically coupled and used to perform a simulation of vessel motions with ART. From the time domain simulation results, the response amplitude operators for sway and roll motions were obtained and compared with the corresponding experimental and numerical results. Because the main purpose of ART was only to reduce roll motions, it was important to show that the natural properties of a floating vessel were not changed by the effects of ART. Various ART filling ratios and several ART positions were considered. In conclusion, ART only reduced the roll motion regardless of its filling ratio and position.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1183-1188
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• 2011

The novel metal position detection method is proposed where conventional techniques, in high temperature, moisture and particle environment, are not able to be applied. It is known that electronic devices, utilizing microwave, ultrasonic or optical technique, are hard to apply for sensing application where temperature is exceeding above 300 degree centigrade. Metal position detection technique, which was consisted with passive elements facing hot sensing surface, utilizing electromagnetic wave was investigated, and the metal detection sensitivity was measured by varying sensor frequency and sensing distance. Measurement result in laboratory test set-up showed position measurement resolution up to 1mm, when distance between two sensing elements were 500mm, and possibility to measure position of hot metal sheet having very high surface temperature.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.41-48
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• 2014

This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1542-1546
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• 2003

Nanotechnology is an important challenge, for which nanoparticle manipulation plays an important role in the assembly of nano elements. In this study, the dynamic equation of system plant is established by van der Waals force, friction, capillary forces etc. To push nanoparticles, strain gauges are used as sensors to actuate an X-Y stage in an atomic force microscopy system. A strategy of pushing nanoparticles is developed based on sliding mode control. Moreover, afuzzy controller is responsible for compensating tip-particle contact loss according to feedback signals of a laser-detector system. According to position control result, experimental results of gold nanoparticle manipulation are presented.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1863-1871
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• 2016

This paper presents an application of fractional order controller for the control of multi input multi output twin rotor aerodynamic system. Dynamics of the considered system are highly nonlinear and there exists a significant cross-coupling between the horizontal and vertical axes (pitch & yaw). In this paper, a fractional order model of twin rotor aerodynamic system is identified using input output data from nonlinear system. Based upon identified fractional order model, a fractional order PID controller is designed to control the angular position of level bar of twin rotor aerodynamic system. The parameters of controller are tuned using Nelder-Mead optimization and compared with particle swarm optimization techniques. Simulation results on the nonlinear model show a significant improvement in the performance of fractional order PID controller as compared to a classical PID controller.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.98-106
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• 2007

The vortex flow characteristics of a double-delta wing, which can change the incidence angle of its apex strake was investigated through the wing-surface pressure measurement and the particle image velocimetry(PIV) measurement of the wing-leeward flow region. The apex strake has sharp edges and can change its incidence angle with a hinge line at the 23% chord position measured from the apex of the main wing. The present study revealed that the incidence-angle change of the apex strake could greatly alter the vortex flow pattern around the double-delta wing and the wing-surface pressure distribution, which suggested that the apex strake could be used as an effective device for the active control of delta-wing vortex flow.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

• Smart Structures and Systems
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• v.20 no.4
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• pp.499-508
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• 2017

The ionic polymer-metal composite (IPMC) is an electroactive polymer material and has a promising potential as actuators for propulsion and locomotion in underwater systems. In this paper a physics based model is used to analyse the actuation dynamics of the IPMC propulsor. Moreover, proportional-integral (PI) controller is used for position control of the tip displacement of IPMC propulsor. PI parameter tuning is performed using particle swarm optimization (PSO) algorithm. Several performance indices have been used as an objective function to optimize the error of the system. Finally, the best tuning method is found out by comparing the results under various performance indices.