• Journal of Power Electronics
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• v.14 no.1
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• pp.125-134
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• 2014

This paper presents a robust and speed-sensorless stator flux estimation for induction motor direct torque control. The proposed observer is based on sliding mode approach. Stator electrical equations are used in the rotor orientation reference frame to eliminate the observer dependence on rotor speed. Lyapunov's concept for systems stability is adopted to confine the observer gain. Furthermore, the sensitivity of the observer to parameter mismatch is recovered with an adaptation technique. The nonlinearities of the pulse width modulation voltage source inverter are estimated and compensated to enhance stability at low speeds. Therefore, a new method based on the model reference adaptive system is proposed. Simulation and experimental results are shown to verify the feasibility and effectiveness of the proposed algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.204-208
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• 2001

Position control of the electro-hydraulic servo indexing system in a flexible forging machine was investigated Flexible forging machine forges an axial type workpiece in the radial direction as well as in the axial direction. The role of the indexing system is to rotate a workpiece fast and accurately to a desired position for continuous shaping. Since the inertia of a workpiece changes during each forging step, a control technique which is robust to inertia variation should be adopted to the position control of the workpiece. In this study, time delayed control technique is applied to the servo system. Time delayed control method does not depend on estimation of specific parameters. Rather, it depends on the direct estimation of a function representing the effect of uncertainties. Direct estimation is accomplished using time delay and the gathered information is used to cancel the unknown dynamics is accomplished using disturbances simultaneously. Experimental result show that the time delayed controller is robust to inertia variation of the load, and satisfactory performance on the sposition accuracy is obtained compared to the contentional feedback control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.990-993
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• 2005

This paper presents new results on designing a robust adaptive direct controller for a class of non-linear first order systems. The designing method based on the use of dead zone in the parameters' update law. It is shown that the size of the dead zone does not depend on the upper bounds of the disturbances. That means that even if the bounds are large, the tracking error will always converge to a set of the dead zone size. However, in the ideal case, when the exogenous signal functions and the function represents un-modeled dynamics of the systems equal to zero, the proposed controller does nt mean the convergence to zero of the tracking error. Computer simulation results show the effectiveness of the controller in dealing with the stated problems.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.214-221
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• 1998

A new control approach using neural network for the robust position control of a BRUSHLESS direct drive(BLDD) motor is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust BLDD motor system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system will be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained by error back-propagation at each sample period to accommodate the possible variations in the parameters or load torque. And the state space analysis is performed to obtain the state feedback gains systematically. In addition, the robustness is also obtained without affecting overall system response.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.75-81
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• 2008

A robust controller is proposed for regulating effectively the pressure of control cylinder of swash plate type variable displacement axial piston pump. In order to design a precise and robust pressure control system, a mathematical model for swash plate control system is identified by the signal compression method. Based on the identified mathematical model, an $H_{\infty}$ robust swash plate controller is designed which is robust to the variation of the load pressure. The precise and robust swash plate control characteristics are verified by experiments.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.37 no.11
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• pp.17-22
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• 2000

A novel and robust direct parameter extraction method for hybrid-p equivalent circuit model of HBT is proposed. A new expression that can accurately resolve the base internal resistance from the measured S-parameters is derived, and it is not sensitive to the values of parasitic access inductance values. Based on the expression, six analytical expressions for the other parameters is developed and these expressions for hybrid-p equivalent circuit modeling ensure robust, fast, and reliable parameter extraction.

• Water Engineering Research
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• v.3 no.3
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• pp.195-202
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• 2002

The mean is generally used as a point estimator in water-quality data. Unfortunately, the nonnormal and skewed distributions of data hinder the direct application of the mean, which is inappropriate statistics in this case. The use of robust statistics such as L, M, and R-estimators are recommended and become more efficient. The median (L-estimator), the biweight (M-estimator), and the Hodges-Lehmann method (R-estimator) are briefly introduced and applied in this paper. From the actual data analyses, it is known that the median does not guarantee robustness for a small number of data sets, and robust measures of location or the arithmetic mean without outliers are highly recommended if the distribution has tails or outliers. Care must be taken to measure the location because water quality level within a water body can change depending on the selected point estimator.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.77-78
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• 2006

A mixed method between $H_2\;and\;H_{\infty}$ control are widely applied to systems which has parameter perturbation and uncertain model to obtain an optimal robust controller. Brushless Direct Current (BLDC) motors are widely used for high performance control applications. Conventional PID controller only provides satisfactory performance for set-point regulation. However, with the presence of nonlinearities, uncertainties and perturbations in the system, conventional PID is not sufficient to achieve an optimal robust controller. This paper presents an approach to ease designing a Mixed $H_2/H_{\infty}$ PID controller for controlling speed of Brushless DC motors and the genetic algorithm is used to solve the optimized problems. Numerical results are shown to prove that the performance in the proposed controller is better than that in the optimal PID controller using LQR approach.

• Journal of Power Electronics
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• v.18 no.3
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• pp.736-745
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• 2018

This paper presents an extended state observer (ESO) based direct torque control (DTC) for use in induction motor systems to handle the issues of time delays, load torque disturbances and parameter uncertainties. Direct torque control offers an excellent torque response and it does not require a proportion integration (PI) controller in the current loop. However, a PI controller is still adopted in the outer speed loop to generate the torque reference value, which is a slow method. An ESO based compound control scheme is proposed to improve the response rate and accuracy of the torque reference signal, especially when load torque is injected. In addition, the time delay problem is analyzed and compensated for in this paper to reduce torque ripples. The proposed disturbance compensation technique based direct control scheme is shown to have good performance both in the transient and stable states via simulations and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.316-321
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• 2003

This paper presents a design method of the wavelet neural network based controller using direct adaptive control method to deal with a stable intelligent control of chaotic systems. The various uncertainties, such as mechanical parametric variation, external disturbance, and unstructured uncertainty influence the control performance. However, the conventional control methods such as optimal control, adaptive control and robust control may not be feasible when an explicit, faithful mathematical model cannot be constructed. Therefore, an intelligent control system that is an on-line trained WNN controller based on direct adaptive control method with adaptive learning rates is proposed to control chaotic nonlinear systems whose mathematical models are not available. The adaptive learning rates are derived in the sense of discrete-type Lyapunov stability theorem, so that the convergence of the tracking error can be guaranteed in the closed-loop system. In the whole design process, the strict constrained conditions and prior knowledge of the controlled plant are not necessary due to the powerful learning ability of the proposed intelligent control system. The gradient-descent method is used for training a wavelet neural network controller of chaotic systems. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with application to the chaotic systems.