• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.222-227
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• 2011

2-axis tracking solar PV system applying a fixed-type unit than in the same area as the panel's power output to more than 140% can be obtained that have been identified. However, this approach compared with fixed or 1-axis control system and control the complexity of trekking equipment power the cursor comes to a relatively small output PV unit is called. In this paper, a small PV power units as a way to improve the economics of the small output of multiple PV units in the central control unit in enclosed places an intermittent manner by a remote control for each unit of the trek at the same time to simplify the control mechanism to reduce power that will be introduced. also the construction of large-scale PV development plans in difficult environments can be utilized in a manner appropriate to introduce.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.967-972
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• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.2-2
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• 2000

This paper presents an adaptive control against uncertainties in tail-controlled STT (skid-to-Turn) missiles. First, we derive an analytic uncertainty model from a parametricaffine missile model developed by the authors. Based on this analytic model, an adaptive feedbacklinearizing control law accompanied by a sliding model control law is proposed. We provide analyses of stability and output tracking performance of the overall adaptive missile system. The performance and validity of the proposed adaptive control scheme is demonstrated by simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.622-631
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• 2001

This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional PID controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.6
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• pp.433-441
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• 2020

This study proposes a constant power tracking algorithm to compensate for the intermittent characteristics of Photovoltaic connected to a DC micro grid. A PV-ESS integrated module in which distributed ESS is additionally connected is utilized for the proposed algorithm. PV performs P&O MPPT control at all times. To supplement the intermittent characteristics of PV, the proposed constant power tracking algorithm maintains constant power by operating the distributed ESS of the PV-ESS integrated module in accordance with the output state of the PV. By performing PSIM simulation and an experiment, this study verifies the performance of the integrated module of PV-ESS for DC micro grids applying the constant power tracking algorithm.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1868-1870
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• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.101-105
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• 1989

The iterative learning controller makes the system output follow the desired output over a finite time interval through iterating trials. In this paper, first we discuss that the design problem of learning controller is originally the design problem of the inverse model. Then we show that the tracking error which is the difference between the desired output and the system output is reduced monotonically by properly modeled inverse system if the magnitude of the learning operator being introduced is bounded within the unit circle in complex domain. Also it would be shown that the conventional learning control method is a kind of extremely simplified inverse model learning control method of the objective controlled system. Hence this control method can be considered as a generalization of the conventional learning control method. The more a designer model the objective controlled system precisely, the better the performance of the approximated inverse model learning controller would be. Finally we compare the performance of the conventional learning control method with that of the approximated inverse model learning control method by computer simulation.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1352-1364
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• 2013

This paper describes a novel structure for single phase Unified Power Quality Conditioner-Distributed Generation (UPQC-DG) with direct grid connected DC-AC converter for low DC output DG systems which can be used not only for compensation of power quality problems but also for supplying of load power partly. This converter has been composed of one full-bridge inverter, one three winding high frequency transformer with galvanic isolation and two cycloconverters. Proper control based on Input Output feedback Linearization is used to tracking the reference signals. The simulation and experimental results are presented to confirm the validity of the proposed approach.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.697-702
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• 2004

In this paper, we proposed that the problem of controlling induction motor with magnetic saturation, is studied from an input-output feedback linearization with adaptive algorithm. is considered. An adaptive input-output feedback linearizing controller is considered under the assumption of known motor parameters and unknown load torque. In order to achieve the speed regulation with the consideration of improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. Simulation results are provided for illustration.