• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.788-791
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• 1996

A mathematical model is developed for thermal solution copolymerization of styrene and acrylonitrile in a continuous stirred tank reactor(CSTR). Computational studies are carried out with the continuous copolymerization system model developed in this work to give the monomer conversion, copolymer composition and the average molecular weights of the copolymer. By performing the dynamic analysis of the reaction system, the polymer properties against the changes in the operating conditions are determined quantitatively. The cascade PID and fuzzy controller show satisfactory performances for both set point tracking and disturbance rejection. Especially, the fuzzy controller is superior to the PID controller.

• Journal of Power Electronics
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• 제16권2호
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• 연구논문집
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• 통권23호
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.583-586
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• 1995

In this paper, a nor fuzzy control algorithm for the target tracking system is proposed, and its characteristics are analyzed and compared with those of the traditional PID controller. Fuzzy rules are generated experimentally using Mamdani's minimum operation and the center of area method. The experimental results prove that the proposed fuzzy algorithm is excellent in our tracking system and its performance is superior to that of the PID controller.

• 수산해양기술연구
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• 제59권1호
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• pp.44-54
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• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• 한국항해항만학회지
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• 제35권5호
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• pp.359-363
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• 2011

본 연구에서는 만타 형상을 가진 무인잠수정(Manta-type unmanned underwater test vehicle)의 제어 성능 평가를 수행 하였다. 제어 방법으로서 PID제어, Fuzzy 제어가 적용되었으며, 6자유도 운동 수학모델과 Matlab Simulink을 이용하여 조종 운동 시뮬레이션을 수행하였다. 또한, 설계된 제어기로 수심제어 및 방위제어에 적용하여, 조류의 외란 하에서 제어 성능을 평가하였다.

• Structural Engineering and Mechanics
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• 제87권3호
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• 한국지능시스템학회논문지
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• 제24권3호
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• pp.279-284
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• 2014

본 논문에서는 최적화 기법과 퍼지 PID제어기를 이용한 자기부상시스템의 부상제어기를 제안한다. 흡인식 자기부상시스템은 일반적으로 비선형 특성을 포함하는 불안정한 시스템이기 때문에 일반적인 선형 제어기를 적용할 경우 우수한 성능을 얻기에는 어려운 점이 있다. 본 논문에서 제안된 제어기는 고정파라미터를 갖는 퍼지 PID제어기를 이용하였으며, 퍼지 PID 제어기 파라미터들은 유전자 알고리즘을 이용하여 최적화를 수행하였으며 유전알고리즘의 목적함수로는 일반적으로 사용되는 성능지수 함수를 사용하였다. 제안된 퍼지 PID 제어기를 적용한 자기부상시스템의 성능을 평가하기 위하여 Matlab을 이용하여 시뮬레이션을 수행하였으며, 고전적 PID제어기와 성능을 비교 분석하였다. 제안된 제어기를 적용한 자기부상시스템의 성능이 고전 PID제어기에 비하여 더 우수한 성능을 보임을 시뮬레이션을 통하여 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.704-707
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• 1997

In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

• Journal of Power Electronics
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• 제16권1호
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• pp.205-216
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• 2016

The manufacturing sector resorts to automation to increase production and homogeneity of products during mass production, without increasing scarce, expensive, and unreliable manpower. Automation in the form of multiple robotic arms that handle materials in all directions in different stages of the process is proven to be the best way to increase production. This paper thoroughly investigates robotic single-arm movements, that is, 360° vertical rotation, with the help of a brushless DC motor, controlled by a fuzzy proportional-integral-derivative (PID) controller. This paper also deals with the design and performance of the fuzzy-based PID controller used to control vertical movement against the limited scope of conventional PID feedback controller and how the torque of the arm is affected by the fuzzy PID controller in the four quadrants to ensure constant speed and accident-free operation despite the influence of gravitational force. The design was simulated through MATLAB/SIMULINK and integrated with dSPACE DS1104-based hardware to verify the dynamic behaviors of the arm.