• 전자공학회논문지SC
• /
• 제44권2호
• /
• pp.24-31
• /
• 2007

본 논문은 신경회로망을 이용한 IPMSM 드라이브의 자기동조 PI 제어기를 제시한다. 일반적으로 수치제어장치 처리는 고정된 이득값을 가진 PI 제어기를 이용한다. 고정된 이득값을 가진 PI 제어기는 어떠한 환경에서는 양호하게 동작할 수 도 있다. 고정된 이득값을 가진 PI 제어기의 강인성을 증가시키기 위하여 신경회로망을 기반으로한 새로운 방법인 STPI 제어기를 제시하였다. STPI 제어기는 속도, 부하토크, 관성과 같은 파라비터가 갑자기 변화하였을 때 오버슈트, 상승시간, 안정화시간을 최소화한다. 또한 본 논문에서는 신경회로망을 이용하여 속도를 제어하고 ANN 제어기를 이용하여 속도를 추정한다. 신경회로망의 역전파 알고리즘 기법은 전동기 속도의 실시간 추정을 제시한다. IPMSM의 속도제어의 결과는 이득값 동조의 효용성을 보여준다. 그리고 STPI 제어기는 고정된 이득값을 가진 PI 제어기에 비하여 강인성 광범위한 운전영역 부하 왜란등에 대하여 우수한 성능을 나타낸다.

• 제어로봇시스템학회논문지
• /
• 제18권12호
• /
• pp.1101-1105
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 제36회 하계학술대회 논문집 B
• /
• pp.1453-1455
• /
• 2005

This paper presents self tuning PI controller of IPMSM drive using neural network. Self tuning PI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 한국정밀공학회지
• /
• 제18권7호
• /
• pp.46-52
• /
• 2001

This study describes the precision control of the torque standard machine using a self-tuning fuzzy controller. The torque standard machine should generate the accurate torque for calibrating a torque sensor. In order to reduce the relative expanded uncertainty of the torque standard machine, when a weight is hanged to the end of the torque arm for generating the torque, the sloped torque arm should be accurately controlled to the horizontal level. If the slope of the torque arm is larger from the inaccurate control, the uncertainty of the torque standard machine due to control will be larger. This applies the inaccurate torque to a torque sensor to calibrate, and the measuring error of the torque sensor generate from it. Therefore the torque arm of the torque standard machine is accurately controlled. In this paper, the self-tuning fuzzy controller was designed using a fuzzy theory, and the torque arm of the torque standard machine was accurately controlled. The control gain of the fuzzy controller, that is the membership function size of the error, the membership function size of the error change and the membership function size of the controller were determined from the self-tuning. The control results of the torque standard machine were the overshoot within 0.0076mm, the rise time within 16.70sec and the steady state error within 0.0076mm.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제51권1호
• /
• pp.8-17
• /
• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
• /
• pp.902-904
• /
• 1988

For a generalized minimum variance controller algorithm the weighting polynomials are are calculated in a way to assign the closed loop poles of the system and to specify the controller gain at a frequency. As a result the oscillations in the control signal may be reduced without changing the deterministic behaviour of the system.

• International Journal of Automotive Technology
• /
• 제4권4호
• /
• pp.181-191
• /
• 2003

Since the nonlinearity and uncertainties which inherently exist in vehicle system need to be considered in active suspension control law design, this paper proposes a new control strategy for active vehicle suspension systems by using a combined control scheme, i.e., respectively using a genetic algorithm (GA) based self-tuning PID controller and a fuzzy logic controller in two loops. In the control scheme, the PID controller is used to minimize vehicle body vertical acceleration, the fuzzy logic controller is to minimize pitch acceleration and meanwhile to attenuate vehicle body vertical acceleration further by tuning weighting factors. In order to improve the adaptability to the changes of plant parameters, based on the defined objectives, a genetic algorithm is introduced to tune the parameters of PID controller, the scaling factors, the gain values and the membership functions of fuzzy logic controller on-line. Taking a four degree-of-freedom nonlinear vehicle model as example, the proposed control scheme is applied and the simulations are carried out in different road disturbance input conditions. Simulation results show that the present control scheme is very effective in reducing peak values of vehicle body accelerations, especially within the most sensitive frequency range of human response, and in attenuating the excessive dynamic tire load to enhance road holding performance. The stability and adaptability are also showed even when the system is subject to severe road conditions, such as a pothole, an obstacle or a step input. Compared with conventional passive suspensions and the active vehicle suspension systems by using, e.g., linear fuzzy logic control, the combined PID and fuzzy control without parameters self-tuning, the new proposed control system with GA-based self-learning ability can improve vehicle ride comfort performance significantly and offer better system robustness.

• Journal of Biosystems Engineering
• /
• 제21권3호
• /
• pp.283-292
• /
• 1996

Automatic guidance of farm tractors would improve productivity by reducing operator fatigue and increasing machine performance. To control tractors within $\pm$5cm of the desired path, fuzzy and adaptive steering controllers were developed to evaluate their characteristics and performance. Two input variables were position and yaw errors, and a steering command was fed to tractor model as controller output. Trapezoidal membership functions were used in the fuzzy controller, and a minimum-variance adaptive controller was implemented into the 2-DOF discrete-time input-output model. For unit-step and composite paths, a dynamic tractor simulator was used to test the controllers developed. The results showed that both controllers could control the tractor within $\pm$5cm error from the defined path and the position error of tractor by fuzzy controller was the bigger of the two. Through simulations, the output of self-tuning adaptive controller was relatively smooth, but the fuzzy controller was very sensitive by the change of gain and the shape of membership functions. Contrarily, modeling procedure of the fuzzy controller was simple, but the adaptive controller had very complex procedure of design and showed that control performance was affected greatly by the order of its model.

• Nuclear Engineering and Technology
• /
• 제27권6호
• /
• pp.833-844
• /
• 1995

증기발생기 수위제어를 위한 자기동조 예측제어기법을 제안하였다. 제어기설계시 측정 가능한 앞되먹임 신호에 대한 고려와 비선형계통이나 시변계통에 적용하기 위해 적응형으로 유도한 것이 제안된 제어기의 특징이다. 이러한 이유로 제안된 제어기는 계통의 동특성에 직접 영향을 주는 앞되먹임 신호가 존재하고, 시간이나 동작조건에 따라 계통의 계수가 변하는 계통에 적용 가능하다. 제안된 제어기의 성능을 검증하기 위해 웨스팅하우스형의 증기발생기 모델을 이용하여 모의실험을 수행하였다. 모의실험 결과 기존의 비례-적분제어기 보다 우수한 성능을 나타냄을 알 수 있었다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1999년도 추계종합학술대회 논문집
• /
• pp.291-294
• /
• 1999

This paper presents a GaAs MESMET self oscillating mixer for high efficiency L-band frequency conversion with small chip area consumption. Main circuit topology is consist of cascoded two FET with resonating part. The circuit is designed as unstably nonlinear for limited frequency band. FET with drain shorted to source is used for frequency tuning element. Linear conversion gain of -18.83 ㏈ is achieved with 9mA and 4V consumption. Input 1㏈ compression point is more than 11㏈m. The chip area is 1.4$\times$1.4 mm.