• 제어로봇시스템학회:학술대회논문집
• /
• 1988.10a
• /
• pp.540-545
• /
• 1988

In this study a microcomputer-aided design program has been developed to design and analysis for the digital adaptive control system. DACS(Digital Adaptive Control System) program has been written in GWBASIC language which is suitable for IBM-PC compatible. The dynamics of each element was modulized and described by linear difference equations. By the aid of this program, sampling time, the number of bits of A/D and D/A converter and the stability for the digital adaptive control system can be determined. In order to estimate the system parameters an on-line identification and a regression analysis method are utilized. The simulation results have been well agreed with the experiments. To demonstrate the utility of this program, an adaptive control system has been designed for air-heating system.

• Smart Structures and Systems
• /
• v.17 no.4
• /
• pp.611-629
• /
• 2016

This study presents a new approach of surrogate modeling for time-consuming finite element analysis. A surrogate model is widely used to reduce the computational cost under an iterative computational analysis. Although a variety of the methods have been widely investigated, there are still difficulties in surrogate modeling from a practical point of view: (1) How to derive optimal design of experiments (i.e., the number of training samples and their locations); and (2) diagnostics of the surrogate model. To overcome these difficulties, we propose a sequential surrogate modeling based on Gaussian process model (GPM) with self-adaptive sampling. The proposed approach not only enables further sampling to make GPM more accurate, but also evaluates the model adequacy within a sequential framework. The applicability of the proposed approach is first demonstrated by using mathematical test functions. Then, it is applied as a substitute of the iterative finite element analysis to Monte Carlo simulation for a response uncertainty analysis under correlated input uncertainties. In all numerical studies, it is successful to build GPM automatically with the minimal user intervention. The proposed approach can be customized for the various response surfaces and help a less experienced user save his/her efforts.

• Journal of Sensor Science and Technology
• /
• v.1 no.2
• /
• pp.155-163
• /
• 1992

The phased array antenna has the ability to perform adaptive sampling by directing the radar beam without inertia in any direction. The adaptive sampling capability of the phased array antenna allows each sampling time interval to be varied for each target, depending on the acceleration of each target at any time. In this paper we design a three-dimensional adaptive tracking algorithm for the phased array radar system with a given set of measurement parameters. The tracking algorithm avoids taking unnecessarily frequent samples, while keeping the angular prediction error within a fraction of antenna beamwidth so that the probability of detection will not be degraded during a track update illuminations. In our algorithm, the target model and the sampling rate are selected depending on the target range and the target maneuver status which is determined by a maneuver detector. A detailed simulation is conducted to test the validity of our tracking algorithm for encounter geometries under various conditions of maneuver.

• Journal of the Korean Society of Industry Convergence
• /
• v.23 no.5
• /
• pp.799-807
• /
• 2020

This paper deals with identification of probabilistic design using reliability based robust optimization in structure design of automatic salt collector. The thickness sizing variables of main structure member in the automatic salt collector were considered the random design variables including the uncertainty of corrosion that would be an inevitable hazardousness in the saltern work environment. The probabilistic constraint functions were selected from the strength performances of the automatic salt collector. The reliability based robust optimum design problem was formulated such that the random design variables were determined by minimizing the weight of the automatic salt collector subject to the probabilistic strength performance constraints evaluating from reliability analysis. Mean value reliability method and adaptive importance sampling method were applied to the reliability evaluation in the reliability based robust optimization. The three sigma level quality was considered robustness in side constraints. The probabilistic optimum design results according to the reliability analysis methods were compared to deterministic optimum design results. The reliability based robust optimization using the mean value reliability method showed the most rational results for the probabilistic optimum structure design of the automatic salt collector.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.9 s.240
• /
• pp.1217-1224
• /
• 2005

To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.353-369
• /
• 2000

We systematized an stratified spatial sample design(SSSD) that uses the adequate stratification criteria such as the shapeness or the dispersion of an interesting region in a spatial population. And we proposed an adaptive searching estimation method in the SSSD to estimate the area of region of interest in two-dimensional surfaces. When wc adopt the proposed adaptive searching estimation method in SSSD, the observing sample size is more decreased than a classical sample design that all the designed sample size is observed. Nevertheless it has been shown that we can produce the moderate result but the efficiency is a slight reduced.

• Journal of Korean Society for Quality Management
• /
• v.38 no.2
• /
• pp.190-201
• /
• 2010

This research proposes a method for designing VSI (Variable Sampling Interval) control charts with supplementary run rules. The basic idea is to apply various run rules and the VSI scheme to a control chart in order to increase the sensitivity. The sampling process of the VSI run rules chart is constructed by Markov chain approach. A procedure for designing the VSI run rules chart is proposed based on Lorenzen and Vance's model. Sensitivity study shows that the VSI run rules charts outperform the FSI (Fixed Sampling Interval) run rules charts for wide range of process mean shifts. A major advantage of the VSI run rules chart over other charts such as CUSUM, EWMA, and adaptive charts is it's simplicity in implementation. Some useful guidelines are proposed based on the sensitivity study.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.148-153
• /
• 1999

In this paper, it is proposed the adaptive-sliding mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Over the past decade, the design of advanced control systems for industrial robotic manipulators has been a very active area of research and two major design categories have emerged. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in continuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple structure is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. Simulation results how that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications of industrial robot control system.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.50 no.3
• /
• pp.130-137
• /
• 2001

In this paper, we propose a new Active Noise Filter Control System which operate as a control performance when a adaptive filter fault. In this system, half-fixed filter which is new filter, connected to parallel with adaptive filter. An adaptive filler use to continuous parameter estimating, but adaptive filter is fault, half-fixed filter update newly data which is continuous estimating date each during sampling period. We simulate and apply the proposed active noise filter system to in the cylinder type duct. Experimental results show that proposed Active Noise Filter Control System has better control performance than existing filter which Eriksson's or Parallel Filter System in term of noise reduction.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.619-621
• /
• 2005

This paper proposes apractical design method for ship-to-ship missiles' autopilot. When the pre-designed analogue autopilot is implemented in digital way, theygenerally suffer from severe performance degradation and instability problem even for a sufficiently small sampling time. Also, aerodynamic uncertainties can affect the overall stability and this happens more severely when the nonlinear autopilot is digitally implemented. In order to realize a practical autopilot, two main issues, digital implementation problem and compensation for the aerodynamic uncertainties, are considered in this paper. MIMO (multi-input multi-output) nonlinear autopilot is presented first and the input and output of the missile are discretized for implementation. In this step, the discretization effect is compensated by designing an additional control input. Finally, we design a parameter adaptation law to compensate the control performance. Stability analysis and 6-DOF (degree-of-freedom) simulations are presented to verify the proposed adaptive autopilot.