• Journal of the Korean Society for Precision Engineering
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• v.22 no.11 s.176
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• pp.64-71
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• 2005

In order to measure surface roughness profile, stylus type equipments are commonly used, but the stylus keeps contact with surface and damages specimens by its tip pressure. Therefore, optics based measurement systems are developed, and light phase interferometer, which is based on light interference phenomenon, is the most noticeable research. However, light interference based measurements require translation mechanisms of nano-meter order in order to generate phase differences or multiple focusing, thus the systems cannot satisfy the industrial need of on-the-machine and in-process measurement to achieve factory automation and productive enhancement. In this research, we focused light reflectance phenomenon rather than the light interference, because reflectance based method do not need translation mechanisms. However, the method cannot direct]y measure surface roughness profile, because reflected light consists of several components and thus it cannot supply surface height information with its original form. In order to overcome the demerit, we newly proposed an image processing based algorithm, which can separate reflected light components and conduct parameterization and reconstruction process with respect to surface height information, and then confirmed the reliability of proposed algorithm by experiment.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.9
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• pp.202-209
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• 2000

In recent years the concern of designing multi-stage gear drives increases with the more application of gear drives in high-speed and high-load. until now however research on the gear drive design has been focused on single gear pairs and the design has been depended on experiences and know-how of designers and carried out commonly by trial and error. We propose the automation of the dimensional design of gears and the configuration design for gear arrangement of two-and three-stage cylindrical gear drives. The dimensional design is divided into two types of design processes to determine the dimensions of gears. The first design process(Process I) uses the total volume of gears to determine gear ratio and uses K factor unit load and aspect ratio to determine gear dimensions. The second one(Process II) makes use of Niemann's formula and center distance to calculate gear ratio and dimensions. Process I and II employ material data from AGMA and ISO standards respectively. The configuration design determines the positions of gears to minimize the volume of gearbox by simulated annealing algorithm. Finally the availability of the design algorithm is validated by the design examples of two-and three-stage gear drives.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.117-127
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• 2007

Many real world control systems usually track several control objectives, simultaneously. At the moment, it is desirable to meet all specified goals using the controllers with simple structures like as proportional-integral (PI) and proportional-integral-derivative (PID) which are very useful in industry applications. Since in practice, these controllers are commonly tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specifications. This paper addresses a new method to bridge the gap between the power of optimal multiobjective control and PI/PID industrial controls. First the PI/PID control problem is reduced to a static output feedback control synthesis through the mixed $H_2/H_{\infty}$ control technique, and then the control parameters are easily carried out using an iterative linear matrix inequalities (ILMI) algorithm. Numerical examples on load-frequency control (LFC) and power system stabilizer (PSS) designs are given to illustrate the proposed methodology. The results are compared with genetic algorithm (GA) based multiobjective control and LMI based full order mixed $H_2/H_{\infty}$ control designs.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.413-423
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• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.424-433
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• 2008

An ownship with towed array sonar (TAS) has limited maneuvers due to its dynamic feature, bearing and frequency measurements of a target which are not detected continuously but are often lost in ocean environment. We propose a pre-processing algorithm for the faded bearing and frequency measurements to solve the BFTMA problem of TAS under limited detection conditions. The proposed pre-processing algorithm to restore the faded bearing and frequency measurements is implemented to perform a BFTMA filter even if the measurements of a target are not continuously detected. The Modified Gain Extended Kalman Filter (MGEKF) method based on the Interacting Multiple Model (IMM) structure is applied for a BFTMA filter algorithm to estimate the target. Simulations for the various conditions were carried out to verify the applicability of the proposed algorithms, and confirmed superior estimation performance compared with the existing Bearings-Only TMA (BOTMA).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.683-686
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• 2002

It is fundamental to count and pack the pills in the medicine manufacture field but those tasks are time and labor consuming. Thus, the need fur automation of those tasks is necessarily getting increased in order to get effective mass production. It Is significant to perceive pills quickly and precisely. There were many trials for this processing but the performance of the existing counting machines varies about size, shape and dispersion tendency of pills. In this paper, the authors try to improve the counting performance of a pill counting machine that has optical sensors with the neural network. The passing signal of pill is acquired with optical sensor and the passage signal of the pill is extracted as input patterns. The gradient and integration of signal during passing time and the time keeping the pill interrupt the light from the LED are used as characteristic feature. The back propagation and perception algorithm are used for training. Experimental results with several pills show that the designed algorithm is a little bit effective to reduce the noise effect which is generated from interference among the machine components and unreliable environment.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.571-582
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• 2008

This paper analyzes global convergence of the univariate dynamic encoding algorithm for searches (uDEAS) and provides an application result to function optimization. uDEAS is a more advanced optimization method than its predecessor in terms of the number of neighborhood points. This improvement should be validated through mathematical analysis for further research and application. Since uDEAS can be categorized into the generating set search method also established recently, the global convergence property of uDEAS is proved in the context of the direct search method. To show the strong performance of uDEAS, the global minima of four 30 dimensional benchmark functions are attempted to be located by uDEAS and the other direct search methods. The proof of global convergence and the successful optimization result guarantee that uDEAS is a reliable and effective global optimization method.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.468-476
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• 2008

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the $\lambda$-P table method is used to calculate ED for the fitness function of GA. The $\lambda$-P table method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with three kinds of ED problems, namely ED considering valve-point effects (EDVP), ED with multiple fuel units (EDMF), and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all three ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.109-116
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• 2005

The design of reconfiguring a class of second-order dynamic systems via proportional plus derivative (P-D) feedback is considered. The aim is to resynthesize a P-D feedback controller such that the eigenvalues of the reconfigured closed-loop system can completely recover those of the original close-loop system, and make the corresponding eigenvectors of the former as close to those of the latter as possible. Based on a parametric result of P-D feedback eigenstructure assignment in second-order dynamic systems, parametric expressions for all the P-D feedback gains and all the closed-loop eigenvector matrices are established and a parametric algorithm for this reconfiguration design is proposed. The parametric algorithm offers all the degrees of design freedom, which can be further utilized to satisfy some additional performances in control system designs. This algorithm involves manipulations only on the original second-order system matrices, thus it is simple and convenient to use. An illustrative example and the simulation results show the simplicity and effect of the proposed parametric method.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.601-614
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• 2006

In this paper, a study on task assignment strategies for a complex real-time network system is presented. Firstly, two task assignment strategies are proposed to improve previous strategies. The proposed strategies assign tasks with meeting end-to-end real-time constraints, and also with optimizing system utilization through period modulation of the tasks. Consequently, the strategies aim at the optimizationto optimize of system performance with while still meeting real-time constraints. The proposed task assignment strategies are devised using the genetic algorithmswith heuristic real-time constraints in the generation of new populations. The strategies are differentiated by the optimization method of the two objectives-meeting end-to-end real-time constraints and optimizing system utilization: the first one has sequential genetic algorithm routines for the objectives, and the second one has one multiple objective genetic algorithm routine to find a Pareto solution. Secondly, the performances of the proposed strategies and a well-known existing task assignment strategy using the BnB(Branch and Bound) optimization are compared with one other through some simulation tests. Through the comparison of the simulation results, the most adequate task assignment strategies are proposed for some as system requirements-: the optimization of system utilization, the maximization of running tasktasks, and the minimization of the number of network node nodesnumber for a network system.