• Nuclear Engineering and Technology
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• v.25 no.2
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• pp.222-232
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• 1993

In this paper, we present two sets of fuzzy algorithms for the steam generator level control ; one for the high power operations where the flow error is available and the other for the low power operations where the flow error is not available. These are converted to a PID type controller for the high power case and to a quadratic function form of a controller for the low power case. These controllers are implemented on the Compact Nuclear Simulator at Korea Atomic Energy Research Institute and tested by a set of four simulation experiments for each. For both cases, the results show that the total variation of the level error and of the flow error are about 50% of those by the PI controllers with about one half of the control action. For the high power case, this is mainly due to the fact that a combination of two PD type controllers in the velocity algorithm form rather than a combination of two PI type controllers in the position algorithm form is used. For the low power case, the controller is essentially a PID type with a very small integral component where the average values for the derivative component input and for the controller output are used.

• Journal of Power System Engineering
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• v.5 no.3
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• pp.104-113
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• 2001

This paper describes a precise position synchronous control of two axes rotating system using BLDC motors and a cooperative control based on decoupling technique and PI control law. The system is required performances both good speed following and minimum position synchronous errors simultaneously. To accomplish these goals, the three kinds of controllers are designed. At first, the current and speed controller are designed very simply to compensate the influences of disturbances and to follow up speed references quickly. Especially, the two degree of freedom PI controller is used considering both good tracking for speed reference input and quick rejection of disturbances in speed controller. Finally, a position synchronous controller is designed as a simple proportional controller to minimize position synchronous errors. The validity of the proposed method is confirmed through some numerical simulations. Moreover, the results are compared to the conventional master-slave control ones to show the effectiveness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.731-736
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• 1994

Experiment on a lab-scale pH process is carried out to evaluate the control performance of the neural linearizing control scheme(NLCS) using a radial basis function(RBF) network which was previously proposed by Kim and Park. NLCS was developed to overcome the difficulties of the conventional neural controllers which occur when they are applied to chemical processes. Since NLCS is applicable for the processes which are already controlled by a linear controller and of which the past operating data are enough, we first control the pH process with PI controller. Using the operating data with PI controller, the linear reference model is determined by optimization. Then, a IMC controller replaces the PI controller as a feedback controller. NLCS consists of the IMC controller and a RBF network. After the learning of the neural network is fully achieved, the dynamics of the process combined with the neural network becomes linear and close to that of the linear reference model and the control performance of the linear control improves. During the training, NLCS maintains the stability and the control performance of the closed loop system. Experimental results show that the NLCS performs better than PI controller and IMC for both the servo and the regulator problems.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.243-251
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• 2003

In this paper, a new model for mobile soccer robot, a type of linear system, is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and plant be well conditioned and the outer loop is a well-known PI controller designed for tracking the reference input, is suggested. Because the plant, the soccer robot, is parameter dependent, it requires the controller to be insensitive to the parameter variation. To achieve this objective, the pole-sensitivity as a pole-variation with respect to the parameter variation is defined and design algorithms for state-feedback controllers are suggested, consisting of two matrices one of which is for general pole-placement and other for parameter insensitive. This paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ cost. By using these properties, we suggest a tuning procedure for the PI controller. We that the control algorithm in this paper, based on the linear system theory, is well work by simulation, and the LPD system modeling and control are more easy treatment for soccer robot.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2240-2245
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• 2003

In this paper, the controller design by coefficient diagram method (CDM) for controlling the trolley position, load-swing angle and hoisting rope length of the overhead crane system simultaneously is proposed. The overhead crane system is a MIMO system consisting of two inputs and three outputs. Its mathematical model is nonlinear with coupling characteristics. This nonlinear model can be approximated to obtain a linear model where the first input mainly affects the trolley position and the load-swing angle while the second input mainly affects the hoisting rope length. In order to utilize the CDM concept for assigning the controllers, namely PID, PD and PI controllers separately, the model is approximated to be three transfer functions in accordance with trolley position, the load-swing angle and the hoisting rope length controls respectively. The satisfied performances of the overhead crane system controlled by the these controllers and fast rejection of the disturbance effect occurred at the trolley position are shown by simulation and experimental results.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.601-611
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• 2017

This paper proposes a simultaneous control of frequency deviation and electric vehicles (EVs) battery state of charge (SOC) using load frequency control (LFC) and EV controllers. In order to provide both frequency stabilization and SOC schedule near optimal performance within the whole operating regions, a multiple-input multiple-output model predictive control (MIMO-MPC) is employed for the coordination of LFC and EV controllers. The MIMO-MPC is an effective model-based prediction which calculates future control signals by an optimization of quadratic programming based on the plant model, past manipulate, measured disturbance, and control signals. By optimizing the input and output weights of the MIMO-MPC using particle swarm optimization (PSO), the optimal MIMO-MPC for simultaneous control of the LFC and EVs, is able to stabilize the frequency fluctuation and maintain the desired battery SOC at the certain time, effectively. Simulation study in a two-area interconnected power system with wind farms shows the effectiveness of the proposed MIMO-MPC over the proportional integral (PI) controller and the decentralized vehicle to grid control (DVC) controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• Advances in Energy Research
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• v.5 no.1
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• pp.79-90
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• 2017

The main objective of load frequency control (LFC) is to keep the frequency value at nominal value and force deviation of the frequency to zero in case of load change. This paper suggests LFC by using a model predictive control (MPC), based on Integral Square Error (ISE) method designed to optimize the damping of oscillations in a two-area power system. The MPC is designed and simulated with a model system in state space, for robust performance in the system response. The proposed MPC is tuned by ISE to achieve superior efficiency. Moreover, its performance has been assessed and compared with the PI and PID conventional controllers. The settling time and overshoot with MPC are extremely minimized as compared with conventional controllers.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.1
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• pp.39-44
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• 1992

Analog PID controllers have been designed to make good use of position control in industries. Recently, the importance of digital position control is emphasized for the requirements of controller which are not only to control the objects but to include various aspects such as easiness of design and implementation, simple exchange of control program and convenient communications of data between various controllers and a host computer. This study proposes a combined control method which is mixed the vaiable structure control (VSC) with the PI control for minimum time position control of DC servo motor by microcomputer. The results of test by this method show offset-free and minimum time optimal position control which is not affected by the disturbance and the system parameter variations. The validity of the proposed method comparing with the conventional PID control is proved by the response experiments.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.820-823
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• 2003

In this paper, we describe a design procedure for cascade controller for induction motor drives based on Genetic Algorithms(GAs). Most electric drives have two separate controllers for current and speed control, which are in general designed in two consecutive steps(firstly the current controller and then the speed controller). We search simultaneously for the couple of discrete anti-windup controllers achieving the optimal compromise of weighted cost and performance indices related to both current and speed responses.