• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.973-983
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• 2015

To improve the control performance of the IPMSM, a novel nonlinear disturbance observer is proposed by using the T-S fuzzy model. A T-S fuzzy model is the combination of local linear models considered at each operating point. Usually the inverse model is easy to obtain in linear systems but not in nonlinear systems. To design a nonlinear disturbance observer, a nonlinear inverse model is obtained based on nonlinear inverse model which is the fuzzy combination of the local linear inverse models. The proposed DOB is used with a PDC controller which is one of the T-S fuzzy controller, and its performance improvement is shown from the simulation results.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.768-776
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• 2000

A robust high-speed motion controller is proposed. The proposed controller consists of the proximate time optimal servomechai는 (PTOD) for high-speed motion, disturbance observer (DOB) for robustness, friction compensator, and saturation handling element, In the proposed controller, DOB basically provides the chance to apply PTOS to non-double integrator systems by drastically reducing disturbances as well as unwanted signals due to difference between real system and the double integrator model. But, in DOB-based systems, if control input is saturated due to control input PTOS and/or DOB, overall system stability cannot be guaranteed. To solve this problem, ribust stability, when the control input is saturated. Eventually, a simple saturation handling element is inserted to maintain internal stability of overall system. Also, we explain the our two saturation handling methods, Additional Saturation Element (ASE_ and Self Adjusting Saturation (SAS), are the equivalent solutions of the saturation problem to maintain internal stability. The stability and performance of the proposed controller are verified through numerical simulations and experiments using a precision linear motor system.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.411-416
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• 2016

This paper presents the design methodology of an unknown input observer for Lipschitz nonlinear systems with unknown inputs in the framework of convex optimization. We use an unknown input observer (UIO) to consider both nonlinearity and disturbance. By deriving a sufficient condition for exponential stability in the linear matrix inequality (LMI) form, existence of a stabilizing observer gain matrix of UIO will be assured by checking whether the quadratic stability margin of the error dynamics is greater than the Lipschitz constant or not. If quadratic stability margin is less than a Lipschitz constant, the coordinate transformation may be used to reduce the Lipschitz constant in the new coordinates. Furthermore, to reduce the maximum singular value of the observer gain matrix elements, an object function to minimize it will be optimally designed by modifying its magnitude so that amplification of sensor measurement noise is minimized via multi-objective optimization algorithm. The performance of UIO is compared to a nonlinear observer (Luenberger-like) with an application to a flexible joint robot system considering a change of load and disturbance. Finally, it is validated via simulations that the estimated angular position and velocity provide true values even in the presence of unknown inputs.

• Journal of Wetlands Research
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• v.17 no.3
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• pp.209-220
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• 2015

This study has improved the existed physical disturbance evaluation assessment technique in a river and analysed its applicability. The improvements are the quantitative evaluation items instead of qualitative one by providing the background and their evaluation equations, corresponding detailed itemization of evaluation score, and the direct input of hydraulic characteristics and geometrical changes by numerical simulation. In order to confirm the applicability of improved disturbance evaluation technique, the comparison and analysis between the evaluation results of existed and improved techniques have been carried out by applying to the 6 cases of natural, urban, and mountainous streams. Direct input of numerical simulation results of HEC-RAS enables the evaluation simple for 8 evaluation items excluding the items of habitat environment and bottom substrate. The improved disturbance evaluation technique, which evaluates the degree of disturbance sensitively by the quantitative and detailed itemized evaluations, has been confirmed the appropriate applicability by applying to river systems.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.379-383
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• 2003

Parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller, consists of a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller, plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that the controller produces rapid and stable responses and overcomes disturbance by using parallel type fuzzy controller in a DC motor application.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.411-418
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• 1999

Generally PI controller is used in the servo system, But the time response of the system which is designed by the PI control scheme is deviated from the desired time response by the system parameter variation or the perturbation like the torque disturbance. LMFC(Linear Model Following Controller) is used to make the response of the system follow that of the model even though the parameter variation or the perturbation exists. In this paper, the design method which uses auxiliary model to construct the robustness enhancer in LMFC is proposed. And this robustness enhancer is designed by robust control theory. The proposed method has facter convergence time against low frequency torque disturbance than LMFC. The results are verified by SIMULINK simulation and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2612-2616
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• 2003

Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.4
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• pp.62-68
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• 1998

In this paper, a speed controller considering the effects of parameter variations and external disturbance for induction motor driver is designed. An proportional plus integral(P1) fuzzy controller is designed to match desired speed tracking specification. Then a robust controller using Fuzzy Weight matrix are designed that in order to reduce the effect of parameter variations caused by external disturbance. The desired speed tracking control performance of the driver is preserved under wide operating range, and also good speed performance is confirmed by the computer simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.