• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.7-11
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• 1991

The adaptive control of flexible joint manipulator is the focus of this paper. The full order flexible joint manipulator dynamic system does not allow the determination of a feedback linearization control as for rigid manipulators. This drawback is overcome by a model order reduction based on a singular perturbation strategy. The full order flexible joint manipulator dynamic model is adopted for derivation of the adaptive control law to damp out the elastic oscillations at the joints. It is shown that the joint position error will converge to zero asymptotically and that other signals remain bounded without precise knowledge of parameters of the manipulator and its joint flexibility.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.3-5
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• 2007

This paper presents decision feedback equalizers using a recurrent neural network trained algorithm using extended Kalman filter(EKF) and sigma-point Kalman filter(SPKF). EKF is propagated, analytically through the first-order linearization of the nonlinear system. This can introduce large errors in the true posterior mean and covariance of the Gaussian random variable. The SPKF addresses this problem by using a deterministic sampling approach. The features of the proposed recurrent neural equalizer And we investigate the bit error rate(BER) between EKF and SPKF.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.4
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• pp.100-108
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• 1992

In this study, the technique of adaptive control based on certainty equivalence for the input-output linearization of nonlinear system is investigated. It is shown that the upper bound of the parameter estimation error can be represented more explicitly than Teel et al's works. Another direct approach, which stows that the adaptive input-output linearing control laws using the normalized identifier yield bounded tracing, is also presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.33-42
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• 1994

The sampling is inevitable in controlling the nonlinear continuous time system. This paper deals with digital feedback linearization problem which eliminates or reduces the effect of the sampling. Necessary and sufficient condition for reducing the sampling error up to O$(h^5)$ are obtained. Also, the effectiveness of our control scheme in accuracy and robustness is shown by comuter simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Journal of the Korean Mathematical Society
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• v.50 no.5
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• pp.1129-1163
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• 2013

Based on finite element discretization, two linearization approaches to the defect-correction method for the steady incompressible Navier-Stokes equations are discussed and investigated. By applying $m$ times of Newton and Picard iterations to solve an artificial viscosity stabilized nonlinear Navier-Stokes problem, respectively, and then correcting the solution by solving a linear problem, two linearized defect-correction algorithms are proposed and analyzed. Error estimates with respect to the mesh size $h$, the kinematic viscosity ${\nu}$, the stability factor ${\alpha}$ and the number of nonlinear iterations $m$ for the discrete solution are derived for the linearized one-step defect-correction algorithms. Efficient stopping criteria for the nonlinear iterations are derived. The influence of the linearizations on the accuracy of the approximate solutions are also investigated. Finally, numerical experiments on a problem with known analytical solution, the lid-driven cavity flow, and the flow over a backward-facing step are performed to verify the theoretical results and demonstrate the effectiveness of the proposed defect-correction algorithms.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.104-114
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• 1995

Mathematical models of industrial robots or manipulators are composed of highly nonlinear equations with nonlinear couplings between the variables of motions. These nonlin- earities were not considered important in the first stage that the working speed of the manipulator was not so fast, but the effect of nonlinear forces has become serious, as the working speed has been increased. So more improvement of performance cannot be expected by the control of manipulator using approximate linearization. As an approach for solving these problems, there is a method that eliminates nonlinear theory, which makes possible cecoupling of coupling terms and arbitrary arranging of poles is briefly introduced in this study. When the theory is applied to design the control law, its feasibility is examined whether the reasonable control results are obtained by simulating position, velocity, torque and tracing trajectory. The relations between the coefficients of the linearized differential equations and the maximum error and torque for the prescribed trajectory are also examined. Finally, the method for selecting the values for getting the most rapid and precise response within maximum torque of each drive is suggested in the choice of coefficients of characteristic equations which are obtained as a result of the control.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.2
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• pp.127-133
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• 2004

A feedforward amplifier, which is composed of several components, is an open loop system. Therefore, feedforward amplifiers are apt to deteriorate its performance according to the environmental changes even though the cancellation performance and the linearization bandwidth of feedforward systems are superior to other linearization methods. A control method is needed for maintaining the original performance of feedforward amplifiers or to keep the desired performance within a little error bounds. In this paper, an adaptive control method using the steepest descent algorithm, which has a good convergence characteristic and is easy to implement, is suggested. The characteristics of the suggested control method compare with the characteristics of other control methods and the simulation results are presented.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.641-646
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• 2014

In this paper, we propose a controller for a ball and beam system which reduces the measurement error effect under AC and DC noise. The ball and beam system measures data through a sensor. If sensor noise is included in a controller via the feedback channel, the signal is distorted and the entire system cannot work normally. Therefore, some appropriate action for the measurement error effect is essential in the controller design. Our controller is equipped with a gain-scaling factor and a compensator to reduce the effect of measurement error in the feedback signal. Effectively, our proposed controller can reduce the AC and DC noise of a feedback sensor. We analyze the proposed controller by Laplace transform technique and illustrate the improved control performance via an experiment for a ball and beam system.