• Journal of Advanced Marine Engineering and Technology
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• v.3 no.1
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• pp.19-31
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• 1979

Recently the adaptive control system, which keeps the control system always optimal by adjusting the control parameters automatically according to the variations of the plant parameters, have become very important in the field of control engineering. The adaptive control systems are usally composed of the plant identification, the decision of the optimal control parameters, and the adjustment of the control parameters. This paper deals with a method of the adaptive control system when PI or PID controller is used in the feed back control system. Its controlled object (the plant) is assumed to be described by the transfer function of $\frac{ke^{-LS}}{1+TS}$ where k, T and L are steady state gain, time constant and pure dead time respectively, and their values are variable in accordance with the change of environmental circumstance. It has been known that a pseudo-random binary signal is quite effective for the measurement of an impulse response of a plant. In adaptive control systems, however, the impulse response itself is not appropriate to determine the control parameters. In this paper, the authors propose a method to estimate directly the parameters of the plant k, T and L by means of the correlation technique using 3 level M-sequence signal as a test signal. The authors also propose a method to determine the optimal parameters of the PI or PID controller in the sense of minimizing the square integral of the control error in the feed back control system, and the values of the optimal parameters are computed numerically for various values of T and L, and the results are examined and compared with those of the conventional methods. Finally the above-mentioned two methods are combined and an algorithm to struct an adaptive control system is suggested. The experiments for the indicial responses by means of both the model of the temperature control system using SCR actuater and the analog simulations have shown good results as expected, and the effectiveness of the proposed method is verified. The M-sequence generator and the time delay circuit, which are manufactured for the experiments, are operated in quite a good condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.4
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• pp.72-78
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• 2009

This paper describes one of the ways how to decide the initial control parameters after the analog type control system is changed to digital control system. If the old control parameters were already known, the initial control parameters for initial operation could be decided easily. But sometimes, it is very difficult for the control system developer to decide initial parameters before plant machine starts up. In that case, if there is a big difference between initial parameters and optimal parameters, the whole plant itself can be in very dangerous conditions. Here is a very simple experimental method which can be very easy but useful to engineers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1462-1469
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• 1997

This study presents a genetic algorithm-based method for optimizing control parameters in fluid power systems. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics. A genetic algorithm seeks control parameters maximizing a measure that evaluates system performance. Five control gains of the PID-PD cascade controller fr an electrohydraulic speed control system with a variable displacement hydraulic motor are optimized using a genetic algorithm in the experiment. Optimized gains are confirmed by inspecting the fitness distribution which represents system performance in gain spaces. It is shown that optimization of the five gains by manual tuning should be a task of great difficulty and that a genetic algorithm is an efficient scheme giving economy of time and in labor in optimizing control parameters of fluid power systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.410-410
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• 2000

Impedance control is recognised as one of the most proper control scheme to carry out the assembly tasks, since it can control the dynamic relationship between the manipulator and environment directly. However, it is well known that the contact force cannot be controlled directly using the impedance control. Also impedance parameters should be properly defined depending on the task to be performed. We propose a new position based impedance control, which has self-adjusted impedance parameters and can control the contact force explicitly, Impedance parameters, as time-varying parameters, are adjusted automatically based on the measured contact force and the position error during the task. A proposed algorithm was implemented on the peg-in-hole task with the industrial manipulator. We shows the effectiveness of proposed control method experimentally.

• Korean Journal of Chemical Engineering
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• v.36 no.3
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• pp.356-367
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• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.518-521
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• 1995

In this paper, a learning control problem is formulated for cooperating multiple-robot manipulators with uncertain system parameters. The commonly held object is also assumed to be unknown and the multiple-robots themselfs experience uncertain operating conditions such as link parameters, viscous friction parameters, suctions, actuator bias, and etc. Under these conditions, the learning controllers designed for learning of uncertain parameters and robot control inputs for multiple-robot systems are shown to drive the multiple-robot manipulators to follow the desired Cartesian trajectory with the desired internal forces to the unknown object.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.4
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• pp.470-477
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• 2000

The states of control loops in existing actual systems are changed according to time varying conditions of controllest process and other system components. Adjusting control parameters properly at site which is performed generally by Ziegler & Nichols mthod is important for safe and efficient operation, but the method may require much time to adjust and not easy to inexperienced engineers. This study is aimed to propose more handy method to adjust control parameters by plotting operating conditions on the space of adjusting parameters. One loop of model control system without perturbation condition has been adopted and its stability limit was plotted on the coordinates of Gain and Integral time which was acquired after analyzing Nyquist diagrams and time domain responses. The result showed that the sets of adjusting parameters according to critical stability and proper stability could be acquired reasonably through both responses and the curves on parameter space revealed available patterns for the purpose of easy maintenance of control characteristics.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.895-900
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• 2008

It is the objective of the present study to conduct correlation analysis for deriving control parameters in vertical shafts using the results obtain by the design of experiments in the preceding research. The control parameters are categorized into objective parameters, derived parameters, condition parameters, operation parameters, and sensing parameters. The maximum pressure in the shaft should be sufficiently small in order to maintain exhaust hood performance. The pressure variations between floors should also be minimized in order to maintain uniform exhaust performance between floors and to save energy for excessive pressure drop in the shaft. The standard deviation based on -4Pa is proposed as an objective parameter to control pressure in shafts. The correlation equation has been obtained between the standard deviation and the sensing parameters of outdoor temperature and the pressure at the top of the shaft.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.932-938
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• 1987

The dynamic equations of robotic manipulators can be derived from either Newton-Euler equation or Lagrangian equation. Model parameters which appear in the resulting dynamic equation are the nonlinear functions of both the inertial parameters and the geometric parameters of robotic manipulators. The identification of the model parameters is important for advanced robot control. In the previous methods for the identification of the model parameters, the geometric parameters are required to be predetermined, or the robotic manipulators are required to follow some special motions. In this paper, we propose an approach to the identification of the model parameters, in which prior knowledge of the geometric parameters is not necessary. We show that the estimation equation for the model parameters can be formulated in an upper block triangular form. Utilizing the special structures, we obtain a simplified least-square estimation algorithm for the model parameter identification. To illustrate the practical use of our method, a 4DOF SCARA robot is examined.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.85-93
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• 2005

This paper is designed a VSI ${\overline{X}}$-CRL synthetic control chart in aspect of economy. We found the optimal sampling interval and various control limit factors under various cost parameters using cost function, proposed Lorenzen and Vance. Optimal design parameters include the sample size, control limit width, sampling interval, CRL/S chart control limit; L. Comparison and analysis of cost parameters are applied between synthetic VSI ${\overline{X}}$-CRL chart and FSI ${\overline{X}}$-CRL chart. The result of this paper shows that VSI ${\overline{X}}$-CRL chart brings cost-cutting effect of 3.04% control expense less than FSI control chart. It may not be difficult to establish the optimal economic control parameters to apply the practical cost parameters in the field.