• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1996-2005
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• 2010

This paper proposes a new method for constant control of the output AC voltage of a voltage-fed three phase Z-source inverter (ZSI), in case of Z-network DC voltage variation or heavy change of load. The modulation index for the reference output AC voltage of ZSI can be calculated by the basic definition of ZSI, the input DC voltage and capacitor voltage of Z-network. And, the output AC voltage of ZSI is controlled by the modified space vector modulation (SVM) with the calculated modulation index. By the proposed method, the modulation index of output AC voltage is closely following in the reference modulation index. The validity of the proposed method is verified using PSIM simulation. In case which the input DC voltage of ZSI is heavily changed from 100[V] to 70[V] (or to 150[V]) and in case which load is changed from $30[\Omega]$ to $10[\Omega]$, we confirmed that the output AC voltage of ZSI is constantly controlled by the proposed method because the modulation index of ZSI is also simultaneously changed. Finally, FFT and %THD of the output voltage and current of ZSI by the proposed method are analyzed.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.798-800
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• 1995

The neural network predictive controller(NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output(Neural Network Predictor) and the other one is for control the plant(Neural Network Controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and prediction error. The NNP forecasts the future output based upon the current control input and the estimated control output. The method is applied to the control of temperature in boiler systems. The proposed NNPC is compared with the other conventional control methods such as PID controller, neural network controller with specialized learning architecture, and one-step-ahead controller. The computer simulation and experimental results show that the proposed method has better performances than the other methods.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.97-99
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• 2007

This paper presents a fuzzy logical control method to implement an on-line optimum efficiency control for Permanent Magnet Synchronous Motor. This method real-timely adjusts the output voltage of the inverter system to achieve the optimum running efficiency of the whole system. At first, the input power is calculated during the steady state in the process of efficiency optimizing. To exactly estimate the steady state of the system, this section needs check up the speed setting on timely. The second section is to calculate input power of dc-bus. The exact measurement of the voltage and current is the vital point to acquire the input power. The third section is the fuzzy logic control unit, which is the key of the whole drive system. Based on the change of input power of dc-bus and output voltage, the variable of output voltage is gained by the fuzzy logical unit. With the on-line optimizing. the whole system call fulfill the minimum input power of dc-bus on the running state. The experimental result proves that the system applied the adjustable V/f control method and the efficiency-optimizing unit possesses optimum efficiency, and it is a better choice for simple variable speed applications such as fans and pump.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.63-67
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• 2004

We know that Neural Network is in use in many control fields. In time of using as controller, Neural Network controller is needed to learning by Input-output pattern. But in many times of control field. we can not get Input-output pattern of Neural Network controller. As a method solving this problem, in this paper, we try New control method that output node of Neural Network bringing control object. Such a New control method application, we can solve the data taking problem to Neural Network controller Input-output. The effectiveness of proposed control algorithm is verified by simulation results of DC servo motor.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.948-950
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• 2003

In this literature, the CMOS current mode fout quadrant differentiator circuit is proposed. The implementation is base on an appropriate input stage that converts the input current into a compressed voltage at the input capacitor ($C_{gs}$) of the CMOS driver circuit. This input voltage use as the control output current which flow to the output node by passing through a MOS active load and use it as the feedback voltage to the input node. Simulation results with level 49 CMOS model of MOSIS are given to demonstrate the correct operation of the proposed configuration. But the gain of the circuit is too low so the output differentiate current also low. The proposed differentiator is expected to find several applications in analog signal processing system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.680-684
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• 2005

This paper presents a data-based stability analysis of a MIMO linear time-invariant discrete-time system, as an extension of the previous results for a SISO system. In the MIMO case, a similar discussion as in the case of a SISO system is also applied, except that an augmented input and output space is considered whose dimension is determined in relation to both the orders of the input and output vectors and the numbers of inputs and outputs. As certain subspaces of the input and output space, both output data space and closed-loop data space are defined, which contain all the behaviors of a system, respectively, with zero input in open-loop and with a control input in closed-loop. Then, we can derive the data-based stability conditions, in which the open-loop stability can be checked by using a data matrix whose column vectors span the output data space and the closed-loop stability can also be checked by using a data matrix whose column vectors span the closed-loop data space.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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• pp.1247-1258
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• 1995

Input-output decoupling is well-known to be effective in the control of the nonlinear systems. This paper points out some problems of this technique in applications, and obtains a new digital input-output decoupling feedback law by using the inherent structure of the system. The effectiveness (accuracy) of our new control technique are confirmed by simple computer simulations. Finally, a digital compensator is also designed. The problems we study are of importance in the field of nonlinear control of robots, aerospace navigation, and vehicular control. The methodology to be employed involves both algebraic and geometric aspects of the systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.209-215
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• 2018

This paper present a 7-level PWM inverter adopting voltage balancing control to series-connected input capacitors. The prior proposed 7-level PWM inverter consists of dc input source, three series-connected capacitors, two bidirectional switch modules, and an H-bridge. This circuit topology is useful to increase the number of output voltage levels, however it fails to generate 7-level in output voltage without consideration for voltage balancing among series-connected capacitors. Capacitor voltage imbalance is caused on the different period between charging and discharging of capacitor. To solve this problem, we uses the amplitude modulation of carrier wave, which is used to produce the center output voltage level. To verify the validity of the proposed control method, we carried out computer-aided simulation and experiments using a prototype.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1037-1041
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• 1996

Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.