• Structural Engineering and Mechanics
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• 제52권2호
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• pp.275-290
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• 2014

In this paper, Simple Adaptive Control (SAC) method is used to mitigate the detrimental effects of earthquakes on MR-damper equipped structures. Acceleration Feedback (AF) is utilized since measuring the acceleration response of structures is known to be reliable and inexpensive. The SAC is simple, fast and as an adaptive control scheme, is immune against the effects of plant and environmental uncertainties. In the present study, in order to translate the desired control force into an applicable MR damper command voltage, a neural network inverse model is trained, validated and used through the simulations. The effectiveness of the proposed AF-based SAC control system is compared with optimal H2/LQG controllers through numerical investigation of a three-story model building. The results indicate that the SAC controller is substantially effective and reliable in both undamaged and damaged structural states, specifically in reducing acceleration responses of seismically excited buildings.

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

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• 제어로봇시스템학회논문지
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• 제14권11호
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• pp.1094-1102
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• 2008

Through the motion control experiment using Industrial Emulator(Model 220 by ECP), the performance comparison of three kinds of controllers such as PID, RIC and LQR was carried out. It was shown that RIC has the best performance in the presence of disturbances such as step one, sinusoidal one and Coulomb friction for the rigid body. LQR using feedback state variables has the best tracking performance far the flexible body. The performance of PID controller is low compared to other controllers, but the design process is simple. The most advanced controller is LQR. In order to attenuate disturbance, an additional state observer should be used to estimate it, making more complex control system. RIC lies between PID and LQR in view of complexity of design. Even though RIC is not complicated, it has good disturbance rejection ability and less tracking error. By considering these aspects, the RIC is suggested as high precision controller to be used in motion control system.

• Journal of Power Electronics
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• 제17권1호
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• pp.181-189
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• 2017

The three-phase four-leg voltage-source inverter topology is an interesting option for the three-phase four-wire system. With an additional leg, this topology can achieve superior performance under unbalanced and nonlinear load conditions. However, because of the low bandwidth of conventional controllers in high-power inverter applications, the system cannot guarantee a balanced output voltage under the unbalanced load condition. Most of the methods proposed to solve this problem mainly use the multiple synchronous frame method, which requires several controllers and a large amount of computation because of frame transformation. This study proposes a simple hybrid controller that combines proportional-integral (PI) and resonant controllers in the synchronous frame synchronized with the positive-sequence component of the output voltage of the three-phase four-leg inverter. The design procedure for the controller and the theoretical analysis are presented. The performance of the proposed method is verified by the experimental results and compared with that of the conventional PI controller.

• 한국지능시스템학회논문지
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• 제16권3호
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• pp.349-356
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• 2006

운반차-막대 시스템을 제어하기 위하여 두 개의 2 차원 퍼지 제어기가 CMAC에 의해 협동하게 하는 제어 계략을 개발하였다. 제어계에서 한 제어기는 운반차의 변위와 속도, 다른 제어기는 막대의 각도와 각속도를 각각의 2 개의 입력 변수로 하고 운반차에 가하는 힘이 두 제어기의 출력 변수인데, 이 변수를 외부의 감독에 따라 CMAC이 학습하게 하여 협동 제어의 효과를 발휘한다. 제어계 구성과 CMAC 훈련에 의한 협동 계략의 단순함에 비하여, 제어계는 4 개의 입력 변수에 의한 퍼지 제어기나 다른 해석적 방법에 의한 것에 비해 손색없는 제어 성능을 보였다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2003년도 춘계전력전자학술대회 논문집(1)
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• pp.404-409
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• 2003

This paper discusses how to generate the reference compensation voltages in Dynamic Voltage Restorers (DVR) by use of PQR power theory Sensed three-phase terminal voltages are transformed to PQR coordinates without time delay. Since the reference voltages in PQR coordinates are do values, the voltage controller for DVRs is simple and easy to design. Proposed control method can be implemented by feedforward controllers or by feedback controllers. This paper verified the theory in the feedforward controller of a DVR by experiments.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.499-502
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• 1996

In this paper, we propose a fuzzy iterative learning controller(FILC). It can control fully unknown dynamic plants through iterative learning. To design learning controllers based on the steepest descent method, it is one of the difficult problems to identify the change of plant output with respect to the change of control input(.part.e/.part.u). To solve this problem, we propose a method as follows: first, calculate .part.e/.part.u using a similarity measure and information in consecutive time steps, then adjust the fuzzy logic controller(FLC) using the sign of .part.e/.part..u. As learning process is iterated, the value of .part.e/.part.u is reinforced. Proposed FILC has the simple architecture compared with previous other controllers. Computer simulations for an inverted pendulum system were conducted to verify the performance of the proposed FILC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.669-675
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• 1991

Based on process analysis as well as extensive operation experience, two fuzzy expert control algorithms, for startup and control, are proposed for a supercritical fluid extraction process which has high interacting multivariable structure. In the proposed algorithms, a new simple defuzzification method which only requires four fundamental arithmetic rules is also presented. Through numerical simulations, control performance using the proposed control algorithm is compared with that of a different fuzzy algorithm by an other researcher and that of conventional PID-type controllers which are tuned by well-known optimal criteria. Also, the proposed control algorithm has been tested to the bench scale supercritical fluid extraction process. As a consequence, the proposed fuzzy expert controller has shown fast and robust control performance while the other controllers show sluggish and/or highly oscillatory responses.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.1141-1144
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• 1999

GPIB-based measurement applications are common in every field of multi-instrument environment. Also personal computers and workstations play a key role in measurement ability to create cost-effective instrument control solutions. For simple data acquisition systems which are automated by GPIB interface, standard GPIB controllers add a little burden to the budget for DAQ. In this paper, we provide software and hardware construction methods for cost-effective custom-made GPIB controller boards both for controllers and instruments. This way of tailored configuration to suit a particular application of GPIB-based instrument control solution pays dividends in cost and flexibility for data processing management.