• Journal of Power Electronics
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• v.15 no.6
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• pp.1456-1467
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• 2015

This paper presents a novel close-loop control scheme based on small signal modeling and weighted composite voltage feedback for a three-phase input and single-phase output Matrix Converter (3-1MC). A small non-polar capacitor is employed as the decoupling unit. The composite voltage weighted by the load voltage and the decoupling unit voltage is used as the feedback value for the voltage controller. Together with the current loop, the dual-loop control is implemented in the 3-1MC. In this paper, the weighted composite voltage expression is derived based on the sinusoidal pulse-width modulation (SPWM) strategy. The switch functions of the 3-1MC are deduced, and the average signal model and small signal model are built. Furthermore, the stability and dynamic performance of the 3-1MC are studied, and simulation and experiment studies are executed. The results show that the control method is effective and feasible. They also show that the design is reasonable and that the operating performance of the 3-1MC is good.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.189-194
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• 1994

Adaptive control systems based upon the command generator tracker(CGT) approach have attracted considerable interest because of the simple structure of its adaptive controller. Some attempts to such improve the adaptive control algorithm, for the sake of the application to broader class of plants, are made. Recently, Su and Sobel(1992) proposed that those schemes can be treated by an unified theory using a metasystem representation with some types of supplementary dynamics. However, in their method, it is difficult to find the dynamic compensator, which is proper and output feedback stabilizable, for the uncertain plant. This paper proposes a new design method of such supplementary dynamics and some parameters of adaptive control system for linear time invariant SISO plants. The method gives a concrete and systematic design method using only a few priori knowledge of the plant.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.29-38
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• 1997

A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.95-100
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• 2001

In this paper, we proposed the robust control scheme for a class of nonlinear dynamical systems using output feedback linearization method. The presented control scheme is based on the VSS. We assume that the nonlinear dynamical system is minimum phase, the relative degree of the system is r＜n and zero dynamics is stable. It is also shown that the global asymtotically stability is guaranted. And we verified that the proposed control scheme Is the feasible through a computer simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.533-534
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• 2013

This paper is concerned with the active vibration control of rectangular plate equipped with MFC actuators. To this end, the dynamic model of the rectangular plate bonded with MFC sensors and actuators was derived by means of the Rayleigh-Ritz method. The MFC actuator and sensor were modeled based on the pin-force assumption. The theoretical model was then validated experimentally. The multiinput and multi-output (MIMO) Positive Position Feedback (PPF) controller was designed based on the natural mode shapes and implemented using dSpace system and Simulink. The proposed control algorithm was applied to the cantilever plate having two MFC wafers having both sensor and actuator. Numerical and experimental investigations were carried out. Both theoretical and experimental result shows that the proposed control algorithm can effectively suppress vibrations of cantilever plate.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_1
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• pp.889-896
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• 2020

We describe a new approach to the analyze the control performance of robotic manipulator based on the monitoring system. The structure of monitoring simulator is consist of seven modes such as control state mode, coordinate mode, input/output mode, program mode, parameters mode, and track mode. The applied control algorithme consists of an time varying feed-forward and feedback controller. The proposed scheme is simple in structure, fast in computation, and suitable for real-time implimemtation. Moreover, this scheme does not require any accurate dynamic modeling and values of parameters. Performance of the proposed monitoring system is illustrated by simulation and experiment for robot manipulator with six degrees of freedom.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.993-996
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• 1993

This paper addresses the structure and its associated learning algorithms of a feedforward multi-layered connectionist network, which has distributed learning abilities, for realizing the basic elements and functions of a traditional fuzzy logic controller. The proposed neural-network-based fuzzy logic control system (NN-FLCS) can be contrasted with the traditional fuzzy logic control system in their network structure and learning ability. An on-line supervised structure/parameter learning algorithm dynamic learning algorithm can find proper fuzzy logic rules, membership functions, and the size of output fuzzy partitions simultaneously. Next, a Reinforcement Neural-Network-Based Fuzzy Logic Control System (RNN-FLCS) is proposed which consists of two closely integrated Neural-Network-Based Fuzzy Logic Controllers (NN-FLCS) for solving various reinforcement learning problems in fuzzy logic systems. One NN-FLC functions as a fuzzy predictor and the other as a fuzzy controller. As ociated with the proposed RNN-FLCS is the reinforcement structure/parameter learning algorithm which dynamically determines the proper network size, connections, and parameters of the RNN-FLCS through an external reinforcement signal. Furthermore, learning can proceed even in the period without any external reinforcement feedback.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.181-187
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• 1996

A frictionless positioning device using cone-shaped active magnetic bearings(AMBs) is developed, which is driven by a brushless DC motor equipped with resolver. The cone-shaped AMB feature that the structure is simple and yet the five d.o.f. rotor motion is controlled by four magnet pairs. A linearized dynamic model, which accounts for the relationship between input voltage and output current in the cone-shaped magnet, is developed and the azimuth motion of the frictionless positioning device is modeled as the second order system. The feedback controller is designed by using linear quadratic regulator with integral action optimal control law so that the cone-shaped AMB system is stabilized and the frictionless positioning device gets the zero steady state. It is observed that the linearized dynamic model is adequate and the frictionless positioning device can achieve the tracking accuracy within the sensor resolution.

• Korean Chemical Engineering Research
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• v.58 no.2
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• pp.190-196
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• 2020

The step to obtain a process dynamic model through process experiments is very important because it needs times and expenditures. Step response method is one of the standard methods to have long been used for understanding process dynamics, obtaining dynamical models and designing control systems. For the step response, it is usually required to measure process output for a step input change in the open-loop manner. Its disadvantage criticized is the long open-loop operation. For this, a method based on the time-optimal control technique to minimize the test time for obtaining the step response has been recently presented. However, the method requires iterative computations for the minimization of test times. Here, a method where iterative computations are not required is proposed. Simulation results are presented to show that test times to obtain step responses are reduced considerably and an autotuning method based on the proposed method is compared with the relay feedback autotuning method accepted widely for the autotuning of controllers.

• Journal of Power Electronics
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• v.16 no.5
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• pp.1629-1638
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• 2016

Differential power processing (DPP) systems are among the most effective architectures for photovoltaic (PV) power systems because they are highly efficient as a result of their distributed local maximum power point tracking ability, which allows the fractional processing of the total generated power. However, DPP systems require a high-efficiency, high step-up/down bidirectional converter with broad operating ranges and galvanic isolation. This study proposes a single, magnetic, high-efficiency, high step-up/down bidirectional DC-DC converter. The proposed converter is composed of a bidirectional flyback and a bidirectional isolated switched-capacitor cell, which are competitively cheap. The output terminals of the flyback converter and switched-capacitor cell are connected in series to obtain the voltage step-up. In the reverse power flow, the converter reciprocally operates with high efficiency across a broad operating range because it uses hard switching instead of soft switching. The proposed topology achieves a genuine on-off interleaved energy transfer at the transformer core and windings, thus providing an excellent utilization ratio. The dynamic characteristics of the converter are analyzed for the controller design. Finally, a 240 W hardware prototype is constructed to demonstrate the operation of the bidirectional converter under a current feedback control loop. To improve the efficiency of a PV system, the maximum power point tracking method is applied to the proposed converter.