• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.160-162
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• 2008

This paper presents the practical pressure control of hydraulic oil-pump system using SR drive for industrial application. In order to get a high performance of pressure dynamics in actual application, a data based PID control scheme is proposed in this paper. The look-up table from pre-measured data produces an approximately proper current reference according to motor speed and oil-pressure. And, PID controller can compensate the pressure error. With the combination of two references, the proposed control scheme can get a fast dynamics and stable operation. Furthermore, the suitable current controller considering the nonlinear characteristics of SRM(Switched Reluctance Motor) and practical test method for data measuring are introduced. The proposed control scheme is verified by the experimental test.

• Journal of IKEEE
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• v.6 no.2 s.11
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• pp.128-135
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• 2002

We use the saturation nonlinear feedback element to generate self-oscillation in order to find an ultimate gain and period of linear plant. The use of saturation nonlinear feedback element can improve accuracy of an ultimate gain and period of unknown linear plant. An ultimate gain and period of linear plant can be used to tune a PID controller parameters. It is possible that an asymmetric oscillation can be occurred under the special circumstances such as with static load disturbance. We analyze an asymmetric self-oscillation. As the results of an analysis, we propose a method to find an ultimate gain and period of linear Plant under the asymmetric self-oscillation.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.567-574
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• 2006

This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.05a
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• pp.96-101
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• 1998

많은 분야에서 널리 사용되고 있는 PID 제어기의 형태는 오차를 갖는 폐루프 시스템으로 구성되며, PID 제어기는 비례, 적분, 미분 제어기로 나누어진다. PID 제어기의 형태가 여러 가지로 제안되고 있지만 보다 중요한 것은 PID 제어기의 파라미터들을 어떻게 적절히 정하느냐 하는 파라미터 조정 문제이다. 실제로 산업 현장에 설치되어 있는 PID 제어기는 대부분 숙련된 기술자에 의해 수동 조작에 의한 시행 착오(trial and error) 법으로 동조되고 있다. 이 경우는 많은 노력과 시간이 소비되고, 외란(disturbance)이 첨가될 경우 적절히 동조된다는 보장도 없다. 본 논문에서는 이러한 문제를 해결하고자 신경회로망을 이용하여 PID 제어기의 파라미터를 동조하는 제어 방법을 제안하였다. 단일 뉴런으로 구성하여 구조가 간단하고, 학습에 의한 성능 개선이 가능하다. 오차 역전파(Error Back-Propagation) 알고리즘에 의하여 PID 파라미터가 되는 가중치를 자동 동조하는 방법이다. 제안한 방식의 유용성을 보이기 위해 DC 서보 모터와 비선형 시스템인 단일 관절 매니퓰레이터를 대상으로 시뮬레이션을 하였다.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.252-261
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• 2013

In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency oscillations under different operating conditions and is superior to the lead-lag damping controller tuned by EA.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.543-550
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• 2014

In many industrial processes and operations, such as power plants, petrochemical industries and ships, shell and tube heat exchangers are widely used and probably applicable for a wide range of operating temperatures. The main purpose of a heat exchanger is to transfer heat between two or more medium with temperature differences. Heat exchangers are highly nonlinear, time-varying and show time lag behavior during operation. The temperature control of such processes has been challenging for control engineers and a variety of forms of PID controllers have been proposed to guarantee better performance. In this paper, a scheme to control the outlet temperature of a shell and tube heat exchanger system that combines the PID controller with feedforward control and anti-windup techniques is presented. A genetic algorithm is used to tune the parameters of the PID controller with anti-windup and the feedforward controller by minimizing the IAE (Integral of Absolute Error). Simulation works are performed to study the performance of the proposed method when applied to the process.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.330-336
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• 2014

Many industrial processes such as continuous stirred tank reactors(CSTRs), desalination plant, distillation columns, pH neutralization processes and so on exhibit highly nonlinear characteristic and time-varying behavior during operation. The control of such processes has been challenging to control engineers. Hence, a variety of forms of PID controllers and their tuning rules for industrial processes have been developed to guarantee the best performance. In this paper, a scheme that designs the practical PID controller with an anti-windup strategy incorporating with an evolutionary algorithm(EA) is presented for the concentration control of a nonisothermal CSTR. EA is used to tune the parameters of the overall PID control process with anti-windup by minimizing the integral of absolute error(IAE). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of using the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.52-55
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• 1996

In order to establish the robust current controller design technique of series wound motor driver system. This paper proposes a method of compensated Bang-Bang current control using a series wound motor driver system under improperly variable load. To get minimum time torque control. A compensated Bang-Bang current controller structure is simpler than the structure of PID plus Bang-Bang controller. This paper shows that a general 8 bits microprocessor be used efficiently implementing such an algorithm. The calculation time of software is extremely small when compared with conventional PID plus Bang-Bang a controller. Both nonlinear operating characteristics of Digital switching elements and Describing Function methods are used for the analysis and synthesis. Real time implementation of compensated Bang-Bang current is achieved. Concept design strategy of the control and PWM waveform generation algorithms are presented in the paper.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.124-133
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• 1996

This paper presents the implementation of variable structure control system for a linear or nonlinear system using neural networks. The overall control system consists of neural network controller and a reaching mode controller. While the former approximates the equivalent control input on the sliding surface, the latter is used to bring the entire system trajectories toward the sliding surface. No supervised learning procedures are needed and the weights of the neural network are tuned on-line automatically. The neural netowrk-based variable structure control system is applied to a nonlinare unstable inverted pendulum system through computer simulations, and implemented using a microcomputer (80486-50MHz) and applied to the DC servomotor position control system. Simulation and experimental results show the expected approximation sliding property is occurred. The proposed controller is compared with a PID controller and shows better performance than the PID controller in abrupt plant parameter change.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.370-372
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• 1994

In this paper, a stable adaptive composite control system consisting of a PID and a fuzzy controllers is designed to control nonlinear systems. In the fuzzy controller, parameters of membership functions characterizing the linguistic terms change according to some adaptive law. Also, parameters of PID controller change according to some adaptive law. These adaptive laws are based on the Lyapunov synthesis approach. Then, it is proved that the closed-loop system using such an adaptive composite control system is globally stable in the sense that all signals involved are bounded and the tracking error converges to zero. We apply this adaptive composite control system to control a nonlinear system.