• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2179-2181
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• 2004

Model-free Method들 중에 반복 피트백 조절 알고리즘(Iterative Feedback Tuning, IFT)는 특정한 성능지수를 정의하고, 이를 최소화하도록 제어기의 게인들을 조절하는 방법을 제시하였다. PID와 같은 고전적인 제어이론에 근거한 제어기 설계 과정과는 달리, IFT 알고리즘은 반복 실험을 통해 성능지수의 Gradient를 구하여 이로부터 필터 게인들 조정하는 방법을 채택하고 있다. 수학적 증명과 실험적 실증을 통하여 IFT의 수렴성과 유용성이 보여짐에도 불구하고 IFT 알고리즘의 한계점은 단일 성능지수의 사용이라는데 있다. 이를 개선하기 위해서는 단일 제어 목적을 위한 단일 성능지수의 사용이 아닌 복수의 제어 목적을 위한 복수의 성능지수의 사용이 필요하다. 본 논문에서는 두 개의 성능지수를 가지는 IFT를 이용해서 위상 여유가 크고, 대역폭이 넓은 제어기를 설계하기 위해서 제어기 게인을 자동 조절하는 알고리즘을 제안하고 ODD에서 사용되는 플랜트에 적용한 모의실험을 통하여 그 유용성을 보였다.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.874-881
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• 2010

A automatic flight control system(AFCS) of UAS needs to control its flight path along target path exactly as adjusts flight coefficient itself depending on static or dynamic changes of airplane's features such as type, size or weight. In this paper, we propose system which tunes control gain autonomously depending on change of airplane's feature in flight as adding MLM(Machine Learning Module) on AFCS. MLM is designed with Linear Regression algorithm and Reinforcement Learning and it includes EvM(Evaluation Module) which evaluates learned control gain from MLM and verified system. This system is tested on beaver FDC simulator and we present its analysed result.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.91-98
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• 2013

The degradation of durability and increase of fatigue on the ship are mainly caused by vibration of the engine and rotating machineries. The damper to minimize the influence from vibration is usually attached between the machineries and its base. General damper applied on the vessel is passive damper which is designed to attenuate specified frequency signals, i.e, high frequency vibration signals. But it is hard to anticipate its performance for low frequency signals. In this research, active vibration isolator using VCM is developed to suppress wide band vibration signals. Routh-Huritz's stable condition, ultimate sensitivity method and parameter tuning are applied to derive PID parameters and 2 and 4 phase choppers are also adapted to drive VCM. Simulation and experiments are executed to confirm the effectiveness of the proposed control schemes.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.157-163
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• 2011

In this paper, configuration control for the Horizontal Maintenance and driving of the mobile inverted pendulum robot has been studied using ARS(Attitude Refrence System). The inverted pendulum technique is getting attention and there have been many researches on the seg-way since the US. Using its 2 freedom, a mobile inverted pendulum robot can move in various modes and Our robot performs goal reaching ARS. Mobile inverted pendulum robot fall down to the forward or reverse direction to converge to the stable point. Kalman Filter is normally used for the algorithm and numerous research is progressing at the moment. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this paper we present a two wheel robot system for an autonomous mobile robot. This paper realized the robot control method which is much simpler but able to get desired performance by using the IMU and PID control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.604-610
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• 2007

Injection molding is the most common method of shaping plastic resins for manufacturing a variety of parts. This injection molding is accomplished by injection molding machines (IMM) which consists of a hewer, a reciprocating screw, barrel assembly, and an injection nozzle. The plastic resin is fed to the machine through the hopper and it should be heated to the target melting temperature, which depends on material properties, as closely as possible with very small temperature overshoot in the barrel. Since the barrel, which has temperature dependent specific heat and thermal conductivity in the operating temperature range, is heated by the several electric heater bands, it is not an easy task to control the temperature of the barrel owing to the interference of neighboring heaters and its material properties. Though PID controller with auto-tuning capability is widely adopted in the nm, the auto-tuning process should be carried out whenever the operating temperature is changed significantly. Recently, though the predictive controller is developed and shows good performance, it has drawbacks: 1. Since the heat transfer modeling process is very complicated and should be carried out again when the barrel is changed, it is somewhat inappropriate in the field. 2. The controller performance is not validated in whole operating temperature range. In this paper, cascade type simple PI controller with input restriction is proposed to find the possibility of controlling the barrel temperature in the whole operating temperature range. It is shown by experiment that the proposed controller shows good performance. This result can be applied to design of PI controller with auto-tuning capability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1462-1469
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• 1997

This study presents a genetic algorithm-based method for optimizing control parameters in fluid power systems. Genetic algorithms are general-purpose optimization methods based on natural evolution and genetics. A genetic algorithm seeks control parameters maximizing a measure that evaluates system performance. Five control gains of the PID-PD cascade controller fr an electrohydraulic speed control system with a variable displacement hydraulic motor are optimized using a genetic algorithm in the experiment. Optimized gains are confirmed by inspecting the fitness distribution which represents system performance in gain spaces. It is shown that optimization of the five gains by manual tuning should be a task of great difficulty and that a genetic algorithm is an efficient scheme giving economy of time and in labor in optimizing control parameters of fluid power systems.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2278-2282
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• 2003

In this paper the structure of 2-DOF controller based on artificial immune network algorithms has been suggested for nonlinear system. Up to present time, a number of structures of the 2-DOF controllers are considered as 2-DOF (2-Degrees Of Freedom) control functions. However, a general view is provided that they are the special cases of either the state feedback or the modification of PID controllers. On the other hand, the immune network system possesses a self organizing and distributed memory, also it has an adaptive function by feed back law to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation, since antibody recognizes specific antigens which are the foreign substances that invade living creatures. Therefore, it can provide optimal solution to external environment. Simulation results by immune based 2-DOF controller reveal that immune algorithm is an effective approach to search for 2-DOF controller.