• Interaction and multiscale mechanics
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• v.5 no.3
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• pp.211-228
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• 2012

This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as a mathematical programming formulation in terms of identification of the design vector, the objective function and the design constraints. Thereafter, the formulated constrained nonlinear multivariable problem is solved with the aid of fmincon: an in-built constrained optimization solver module available in MatLab. In order to gain experience, a synthetic case-study is considered wherein key issues such as the determination and setting up of variable bounds, global optimality of the solution and minimum number of data-points required for prediction of parameters is addressed. The results reveal that the developed technique is quite efficient in predicting the model parameters. The best result is obtained when the design variables are subjected to a lower bound without any upper bound. Global optimality of the solution is achieved using the developed technique. A minimum of 4-5 randomly selected data-points are required to achieve the optimal solution. The above technique has also been adopted for real-time settlement of four oil refineries with encouraging results.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.110-110
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• 2001

By the state transformation including independent outputs functions, a nonlinear process model can be decomposed into two subsystems; the one(design model) is described in output variables as new states and used for control system synthesis and the other(disturbance model) is described in the original unavailable states and its couplings with the design model are treated as uncertain time-varying parameters in the design model. Its existence with respect to the design model is ignored. So, the design model is and uncertain time-variant system. Control synthesis based on a reduced design model is a combined form of a time-variant input-output linearization with parameter estimation. The parameter estimation is also based on the design model and it gives the parameter estimates such that the estimated outputs follow the actual outputs in a specified way. The disturbances form disturbance model and as well all the other uncertainties affecting the outputs will be reflected into the estimated parameters used in the linearizing control law.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.276-283
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• 2012

In this paper, a practical quasi-optimal DOA(direction of arrival) estimator is proposed in order to develop a one-axis gimbaled ultrasonic source tracker for mobile robot applications. With help of the gimbal structure, the ultrasonic moving source tracking problem can be simply reduced to the DOA estimation. The DOA estimation is known as one of the representative long-pending nonlinear filtering problems, but the conventional nonlinear filters might be restrictive in many actual situations because it cannot guarantee the reliable performance due to the use of nonlinear signal model. This motivates us to reformulate the DOA estimation problem in the linear robust state estimation setting. Based on the assumption that the received ultrasonic signals are noisy sinusoids satisfying linear prediction property, a linear uncertain measurement model is newly derived. To avoid the DOA estimation performance degradation caused by the stochastic parameter uncertainty contained in the linear measurement model, the recently developed NCRKF (non-conservative robust Kalman filter) scheme [1] is utilized. The proposed linear DOA estimator provides excellent DOA estimation performance and it is suitable for real-time implementation for its linear recursive filter structure. The effectiveness of the suggested DOA estimation scheme is demonstrated through simulations and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.48.2-48
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• 2002

This paper presents an integrated sliding mode adaptive control scheme for general nonlinear uncertain systems, where structured uncertainty is assumed can be linearly parameterized and unstructured uncertainty is assumed be bounded by unknown constant A certain estimation scheme for this unknown constant is introduced to attenuate the unstructured uncertainty. Presented control scheme is shown to be stable and numerical expressions of bounds of all error signals are given, from which we can acquire some useful information about practical trade-off between tracking performance and parameter estimation property.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.3
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• pp.21-26
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• 2010

This paper deals with the precise parameter estimation of an air vehicle without a priori information. First, Recursive Least Squares technique, which is an equation error method and does not require any a priori information, is applied and then the extended Kalman filter is used to tune parameters more precisely. To show the performance, a nonlinear longitudinal missile model is simulated and the parameters are estimated. The results show that this consecutive application of the techniques gives a very good estimation performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.18-25
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• 2007

Linear motor is easily affected by load disturbance, force ripple, friction, and parameter variations because there is no mechanical transmission to reduce the effects of model uncertainties and external disturbance. These nonlinear effects have been reduced for high-speed/high-accuracy position control either through the better motor design or via the better control algorithm that can compensate the nonlinear effects. In this paper, a nonlinear adaptive control algorithm is designed and applied for the position control of permanent magnet linear synchronous motor. In order to estimate and compensate the nonlinear effects such as friction and force ripple, the estimation and the nonlinear adaptive control laws are derived based on the virtual control input and a suitable Lyapunov function. The proposed controller is evaluated through the computer simulations. The control algorithm is also implemented to a DSP board and interfaced to the PMLSM for verifying the realtime control performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2255-2262
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• 2008

This paper presents a design parameter calculation methodology and its realization to construction for the damped oscillatory impulse current generator(ICG) modelled as damping factor $\alpha$. Matlab internal functions, "fzero" and "polyfit" are applied to find a which are solutions of second order nonlinear equation related with three wave parameters $T_{1},T_{2}$ and $I_{os}$. The calculation results for standard impulse current waveforms such as 4/10${\mu}s$, 8/20${\mu}s$ and 30/80${\mu}s$ show very good accuracy and this results make it possible to extend to generalization in the design of damped oscillatory lCG with any capacitor. 8/20${\mu}s$ ICG based on the calculated design circuit parameters is fabricated in consideration of the nonlinear load(MOV) variation. Comparisons of the tested waveforms with the designed estimation show error within 10% for the waveform tolerance recommended in IEC 60060-1 and IEEE std. C62.45.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.913-917
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• 2009

The measures of leverage in linear regression has been extended to nonlinear regression models. We consider several curvature measures of nonlinearity in an estimation situation. The relationship between measures of leverage and statistical curvature are explored in nonlinear regression models. The circumstances under which the Jacobian leverage reduces to a tangent plane leverage are discussed in connection with the effective residual curvature of the nonlinear model.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.80-84
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• 2000

Network parameters in power systems are indispensable for all of power system engineering studies, including the power flow calculation and the state estimation. The network parameters required for the studios, in general, are estimated by using several estimation techniques, since it Is very difficult to measure. To improve the estimation accuracy of the network parameters, this paper adopt the synchronized phasor measurements which are acquired from the Phasor Measurement Unit with built-in GPS receiver. In this paper, the parameter estimation problem is formulated with over-determined nonlinear measurement equations and solved with Newton-Raphson method and pseudo-inverse. The effectiveness of the proposed parameter estimation with the synchronized phasor measurements is verified through some case studies with IEEE sample system. The results are very promising.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2439-2450
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• 1997

As recording densities increase in digital magnetic recording channels, the performances of digital detection techniques such as PRML and DFE degrade significantly due to nonlinear distortion in recording channels. The primary impediments for hgih-density recording are generally classified as nonlinear transition shift, which can be reduced substantially by the precompensation technique, and partial erasure which usually requires sophisticated nonlinear equalization techniques. In order to acheieve the highest density recording, accurate estimation of the parameters associated with these two noninear distortions is crucial. In this paper, a new estimation technique to distinguish these two different nonlinear effect using a proposed adaptive algorithm in time domain is presented. The effectiveness of the proposed adaptive approach to identify uniquely the nonlinear parameter with bias is demonstrated by computer simulation.