• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.825-829
• /
• 2005

This paper presents an approach for designing a fuzzy logic-based adaptive SVC damping In controller for damping low frequency power oscillations. Power systems are often subject to low Frequency electro-mechanical oscillations resulting from electrical disturbances. Generally, power system stabilizers are designed to provide damping against this kind of oscillations. Another means to achieve damping is to design supplementary damping controllers that are equipped with SVC. Various approaches are available for designing such controllers, many of which are based on the concepts of damping torque and others which treat the damping controller design as a generic control problem and apply various control theories on it. In our proposed approach, linear optimal controllers are designed and then a fuzzy logic tuning mechanism is constructed to generate a single control signal. The controller uses the system operating condition and a fuzzy logic signal tuner to blend the control signals generated by two linear controllers, which are designed using an optimal control method. First, we design damping controllers for the two extreme conditions; the control action for intermediate conditions is determined by the fuzzy logic tuner. The more the operating condition belongs to one of the two fuzzy sets, the stronger the contribution of the control signal from that set in the output signal. Simulation studies done on a one-machine infinite-bus and a four-machine two-area test system, show that the proposed fuzzy adaptive damping SVC controller effectively enhances the damping of low frequency oscillations.

• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.281-286
• /
• 2005

The main objective of the research work presented in this article is to present a systematic approach for designing a multilayer feed-forward artificial neural network based self-tuning power system stabilizer (ST-ANNPSS). In order to suggest an approach for selecting the number of neurons in the hidden layer, the dynamic performance of the system with ST-ANNPSS is studied and hence compared with that of conventional PSS. Finally the effect of variation of loading condition and equivalent reactance, Xe is investigated on dynamic performance of the system with ST-ANNPSS. Investigations reveal that ANN with one hidden layer comprising nine neurons is adequate and sufficient for ST-ANNPSS. Studies show that the dynamic performance of STANNPSS is quite superior to that of conventional PSS for the loading condition different from the nominal. Also it is revealed that the performance of ST-ANNPSS is quite robust to a wide variation in loading condition.

• Computers and Concrete
• /
• 제30권5호
• /
• pp.357-367
• /
• 2022

In this paper, we propose an efficient control method that can be transformed into a general building control problem for building structure control using these reliability criteria. To facilitate the calculation of controller H∞, an efficient solution method based on Linear Matrix Inequality (LMI) is introduced, namely H∞-based LMI control. In addition, a self-tuning predictive grey fuzzy controller is proposed to solve the problem caused by wrong parameter selection to eliminates the effect of dynamic coupling between degrees of freedom (DOF) in Self-Tuning Fuzzy Controllers. We prove stability using Lyapunov's stability theorem. To check the applicability of the proposed method, the proposed controller is applied and the control characteristics are determined. The simulation assumes system uncertainty in the controller design and emphasizes the use of acceleration feedback as a practical consideration. Simulation results show that the performance of the proposed controller is impressive, stable, and consistent with the performance of LMI-based methods. Therefore, an effective control method is suitable for seismic reinforcement of civil buildings.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1992년도 추계학술대회 논문집
• /
• pp.182-186
• /
• 1992

A self tuning technique is derived for PID controllers which are widely used in industries. The tuning algorithm is based upon a fuzzy indirect reasoning method and an iterative technique. The fuzzy technique is considered to obtain ease and simplicity of tuning process. The PID gains for the first tuning action are determined by a method which is modified from the Ziegler-Nichols step response method. The first PID gains are determined to obtain a control performance so close to a design performance that the followed tuning process can be made effectively. The design parameters are given as time-domain variables which human is familiar with. The results of simulation studies show that the proped tuning method can produce an effective tuning for arbitaray design performances.

• 전자공학회논문지SC
• /
• 제44권6호
• /
• pp.1-10
• /
• 2007

본 논문에서는 비선형 다변수 시스템에 적응할 수 있는 신경회로망을 이용한 PID 구조를 갖는 직접 다변수 자기동조 제어기를 제안한다. 제어기에 적용되는 플랜트는 잡음, 시간지연과 상호결합항이 존재하며 파라미터가 변하는 비선형 다변수 시스템이다. 비선형 다변수 시스템은 선형부분과 비선형부분으로 분리한 형태로 구성되며, 선형제어기는 외부환경 변화에 적응할 수 있는 PID 제어기 특성을 가진 자기동조 PID 제어기 이다. 선형부분의 제어기 파라미터는 순환최소자승법으로 직접 추정하고 비선형 부분의 파라미터는 신경회로망으로 추정한다. 그리고 각 부분에서 추정한 파라미터를 합한 후 비선형 다변수 일반화 자기동조 제어기의 제어법칙에 적용한다. 제어 알고리듬의 타당성을 확인하기 위해 시간 지연이 있고 일정한 시간이 경과한 후 시스템의 파라미터가 변하는 비선형 다변수 시스템에 대해 컴퓨터 시뮬레이션을 하였다. 또한 기존의 신경회로망을 이용한 직접 다변수 적응 제어기에 비해 효과적이다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
• /
• pp.236-241
• /
• 1988

This note considers the class of controllers with integral action which arise directly from appropriate system models. Via internal model principle approach, a corresponding class of self-tuning controller is shown to have both integral action in controller and offset removal in the tuning algorithm. The key idea is to constrain the estimator in each step in order to ensure that dc gain of feedforward and feedback polynomial of adaptive controller are always equal, thus allowing the loop integrator to work properly.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
• /
• pp.127-130
• /
• 1995

Fuzzy controllers have proven to be powerful in controlling dynamic processes where mathematical models are unknown or intractable and ill-defined. The way of improving the performance of a fuzzy controller is based on making up rules, constructing membership functions, selecting a defuzzification method and adjusting input-output scaling factors. But there are many difficulties in tuning those to optimize a fuzzy controller. So, in this paper, we propose the look-up table based self-orgenizing fuzzy controller (LSOFC) which optimizes look-up values resulting from the above fuzzy processes. We use the plus-minus tuning method(PMTM), scanning the value through the processes of addition and subtraction. Simulation results demonstrate that the performance of LSOFC is far better than that of a non-tuning fuzzy controller.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
• /
• 제54권8호
• /
• pp.395-401
• /
• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gam 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.

• 융합신호처리학회논문지
• /
• 제4권4호
• /
• pp.52-57
• /
• 2003

PID제어기의 파라미터의 조정 방법이 전문가의 경험적 지식과 플랜트 스텝응답 파형 모양에 기초하여 퍼지 싱글톤 추론에 의해 행하는 방법을 나타내었다. 파라미터 조정방법은 두 레벨이 있다. 높은 레벨은 모델링 할 수 없는 플랜트 특성에 대하여 전문가의 Know-how에 기초하여 제어기의 수정계수를 결정하는 것이다. 저 단계는 Ziegler-Nichol 의 한계 감도법의 응답 특성에 의해 특정 계수를 결정한다. 마지막 단계는 량과 제어응답 파형의 면적법에서 얻은 특정량에서 조정 규칙으로 취하고 퍼지추론에 수정 계수와 특정계수로 조정규칙을 만들어 퍼지 싱글톤 추론에 의해 PID제어기의 각 파라미터를 적정한 값으로 자동조정 하는 법을 나타내었다.