• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1173-1177
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• 1990

Cerebellar Model Linear Associator Net(CMLAN), a kind of neuro-net based adaptive control function generator, was applied to the problem of direct inverse calibration of three and six d.o.f. POMA 560 robot. Since CMLAN autonomously maps and generalizes a desired system function via learning on the sampled input/output pair nodes, CMLAN allows no knowledge in system modeling and other error sources. The CMLAN based direct inverse calibration avoids the complex procedure of identifying various system parameters such as geometric(kinematic) or nongeometric(dynamic) ones and generates the corresponding desired compensated joint commands directly to each joint for given target commands in the world coordinate. The generated net outputs automatically handles the effect of unknown system parameters and dynamic error sources. On-line sequential learning on the prespecified sampled nodes requires only the measurement of the corresponding tool tip locations for three d.o.f. manipulator but location and orientation for six d.o.f. manipulator. The proposed calibration procedure can be applied to any robot.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.121-127
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• 2010

This paper relates with the improved CMA blind adaptive equalization algorithm which uses the constellation matching method that improve the inverse modelling efficiency of a communication channel compared to the present CMA blind adaptive equalizer. The amplitude distortion can be compensated in the present CMA blind adaptive equalizer which is used for the reduction of intersymbol interference by distortion that generate such as a band limited wireless mobile channel, but in the improved adaptive alogorithm operates with the minimize the amplitude phase distortion in the output of equalizer by applying the cost function that is composition of additional signal constellation matching error terms. In order to evaluation of the inverse modeling efficiency of improved algorithm, the residual intersymbol interference and recovered signal constellation were compared by computer simulation. As a result of comparion of computer simulation, the improved algorithm has a good stability in the residual intersymbol interference in the steady state, but it has a slow convergence rate in the adaptation state in initial state.

• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.13-22
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• 1989

Underwater channels can be regarded as time-varying systems in view of the acoustical characteristics due to the fact that the characteristics of the channel are affected by the environmental and geometrical conditions. Especially in shallow water case, the surface and bottom conduct as a waveguide so echo effect due tu the multipath reflections are severe. Therefore in shallow water communications, it is very important to equalize the transmitted signals distorted by the underwater channels with time-varying multipath fading. In this paper an equalizer system which employs the frequency domain adaptive filter to equalize the channels using inverse modeling technique is introduced.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.295-303
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• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.348-353
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• 1994

Magnetic Servo Levitation (MSL) has been proposed as a method to drive a fast-tool servo system. This paper discusses some fundamental control and modeling issues in the development of a long-range high-bandwidth fast-tool servo based on MSL. A resursive linear model is developed to describe the system's dynamics linear model is developed to describe the system's dynamics, and further used to discuss controller design. For a given controller architecture, the performance of two controllers is then compared, one based on an approximation to the inverse plant dynamics, the second based on a adaptive neural network.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.215-226
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• 2016

Modeling, control and implementation of a real redundant robot with five Degrees Freedom (DOF) of the SCARA (Selective Compliant Assembly Robot Arm) manipulator type is presented. Through geometric methods and structural and functional considerations, the inverse kinematics for redundant robot can be obtained. By means of a modification of the classical sliding mode control law through a hyperbolic function, we get a new algorithm which enables reducing the chattering effect of the real actuators, which together with the learning and adaptive controllers, is applied to the model and to the real robot. A simulation environment including the actuator dynamics is elaborated. A 5 DOF robot, a communication interface and a signal conditioning circuit are designed and implemented for feedback. Three control laws are executed in: a simulation structure (together with the dynamic model of the SCARA type redundant manipulator and the actuator dynamics) and a real redundant manipulator of the SCARA type carried out using MatLab/Simulink programming tools. The results, obtained through simulation and implementation, were represented by comparative curves and RMS indices of the joint errors, and they showed that the redundant manipulator, both in the simulation and the implementation, followed the test trajectory with less pronounced maximum errors using the adaptive controller than the other controllers, with more homogeneous motions of the manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.129.4-129
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• 2001

The looper control of hot strip finishing mill is one of the most important control item in hot strip rolling mill process. Loopers are placed between finishing mill stands and control the mass flow of the two stands. Another important action of the looper is to control the strip tension which influences on the width of the strip. So it is very important to control both the looper angle and the strip tension simultaneously but the looper angle and the strip tension are strongly interacted by each other. There are many control schemes such as conventional, non-interactive, LQ(Linear Quadratic), Hinf and ILQ(Inverse Linear Quadratic), Adaptive(gain scheduling) control in the looper control system. In this paper, we present the modeling for the looper of a hot strip finishing mill to control the tension of the strip and suggest another control method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.948-951
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• 1996

High-speed/high-accuracy control of robot manipulator becomes more and more stringent because of the external disturbance and nonlinear characteristics. To meet this ends, lots of control strategies were proposed in the past such as the computed torque control, the nonlinear decoupled feedback control, and adaptive control. These control methods need computations of the inverse dynamics and require much computational effort. Recently, a disturbance observer with unmodeled robot dynamics and simple algorithms to motion control have been widely studied. This paper proposes a motor control strategy based on the disturbance observer which estimate the disturbance of each joint from input-output relationship of the actuator and eliminate the estimated disturbance including the torque due to modeling errors, coupling force, nonlinear friction, and so on. To apply the disturbance observer to closedloop system like velocity servo pack, the modified control structure was constructed and shown that it is equivalent to a disturbance observer in open-loop system. Finally, using the proposed approach, simulation and experiments were carried out for a two-degree-of-freedom SCARA type direct drive robot, and show some results to verify the effectiveness of the proposed algorithms.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.681-695
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• 2019

A Transient Storage Model (TSM) is one of the most widely used model accounting for complex solute transport in natural river to understanding natural river properties with four TSM key parameters. The TSM parameters are estimated via inverse modeling. Parameter estimation of the TSM is carried out by solving optimization problem about finding best fitted simulation curve with measured curve obtained from tracer test. Several studies have reported uncertainty in parameter estimation from non-convexity of the problem. In this study, we assessed best combination of optimization method and objective function for TSM parameter estimation using Cheong-mi Creek tracer test data. In order to find best optimization setting guaranteeing convergence and speed, Evolutionary Algorithm (EA) based global optimization methods, such as CCE of SCE-UA and MCCE of SP-UCI, and error based objective functions were compared, using Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL). Overall results showed that multi-EA SC-SAHEL with Percent Mean Squared Error (PMSE) objective function is the best optimization setting which is fastest and stable method in convergence.