• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권4호
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• pp.271-276
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• 2006

To implement a generalization of value functions in Adaptive Search Element (ASE)-reinforcement learning, CMAC (Cerebellar Model Articulation Controller) is integrated into ASE controller. ASE-reinforcement learning scheme is briefly studied to discuss how CMAC is integrated into ASE controller. Neighbourhood Sequential Training for CMAC is utilized to establish the look-up table and to produce discrete control outputs. In computer simulation, an ASE controller and a couple of ASE-CMAC neural network are trained to balance the inverted pendulum on a cart. The number of trials until the controllers are established and the learning performance of the controllers are evaluated to find that generalization ability of the CMAC improves the speed of the ASE-reinforcement learning enough to realize the cartpole control system.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.246-254
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied for a Process control system by immune algorithm. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. Also, a number of approaches have been proposed to implement mixed control structures that combine a PID controller with fuzzy logic. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Since the immune system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (Parallel Distributed Processing) network to complete patterns against the environmental situation. Simulation results reveal that reference model basd tuning by immune network suggested in this paper is an effective approach to search for optimal or near optimal process control.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.494-501
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• 2001

In this paper an ANFIS(Adativo Neuro-Fuzzy Inference System)- based fault detection and diagnosis for a closed loop control system is proposed. The proposed diagnostic system contains two ANFIS. One is run as a parallel model within the model in closed loop control(MCL) and the other is run as a series-parallel model within the process in closed loop(PCL) for the generation of relevant symptoms for fault diagnosis. These symptoms are further processed by another classification logic with simple rules and neural network for process and controller fault diagnosis. Experimental results for a DC shunt motor control system illustrate the effectiveness of the proposed diagnostic scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1128-1131
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• 2003

This paper proposes a speed control system based on a fuzzy logic approach, integrated with a simple and effective adaptive algorithms. And this paper attempts to provide a thorough comparative insight into the behavior of induction motor drive with PI, direct and improved fuzzy speed controller. A indirect vector controlled induction motor is simulated under varying operating condition. The validity of the comparative results is confirmed by simulation results for induction motor drive system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 B
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• pp.727-728
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• 2006

This paper is proposed robust control based on the vector controlled induction motor drive with adaptive fuzzy learning control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed estimation of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Journal of Mechanical Science and Technology
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• 제17권2호
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• pp.187-196
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• 2003

In this paper, a new methodology of evolutionary computations - An Adaptive Evolutionary Algorithm (AEA) is proposed. AEA uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations : global search capability of GA and local search capability of ES. In the reproduction procedure, the proportions of the population by GA and ES are adaptively modulated according to the fitness. AEA is used to. designing fuzzy logic controller (FLC) for a high-angle-of-attack flight system for a super-maneuverable version of F-18 aircraft. AEA is used to determine the membership functions and scaling factors of an FLC. The computer simulation results show that the FLC has met both robustness and performance requirements.

• Journal of Power Electronics
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• 제13권1호
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• pp.139-160
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• 2013

In this paper, an intelligent robust control system (IRCS) for precision tracking control of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The IRCS comprises a recurrent wavelet-based interval type-2 fuzzy-neural-network controller (RWIT2FNNC), an RWIT2FNN estimator (RWIT2FNNE) and a compensated controller. The RWIT2FNNC combines the merits of a self-constructing interval type-2 fuzzy logic system, a recurrent neural network and a wavelet neural network. Moreover, it performs the structure and parameter-learning concurrently. The RWIT2FNNC is used as the main tracking controller to mimic the ideal control law (ICL) while the RWIT2FNNE is developed to approximate an unknown dynamic function including the lumped parameter uncertainty. Furthermore, the compensated controller is designed to achieve $L_2$ tracking performance with a desired attenuation level and to deal with uncertainties including approximation errors, optimal parameter vectors and higher order terms in the Taylor series. Moreover, the adaptive learning algorithms for the compensated controller and the RWIT2FNNE are derived by using the Lyapunov stability theorem to train the parameters of the RWIT2FNNE online. A computer simulation and an experimental system are developed to validate the effectiveness of the proposed IRCS. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulation and experimental results confirm that the IRCS grants robust performance and precise response regardless of load disturbances and PMSM parameters uncertainties.

• 방송공학회논문지
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• 제22권5호
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• pp.618-631
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• 2017

본 논문에서는 시변 네트워크 상황에서 끊김 없는 미디어 서비스를 제공 할 수 있는 퍼지 논리 기반 DASH 적응 알고리즘(FDASH)의 수정을 제안한다. 제안하는 알고리즘은 퍼지 논리 제어부(FLC : Fuzzy Logic Controller)의 수정을 통하여 다음 요청 할 세그먼트의 비트율에 대해 최적의 판단을 하도록 하고, 세그먼트 비트율 필터링 모듈(SBFM : Segment Bit-rate Filtering Module)을 적용하여 비디오 화질의 변화 횟수를 줄인다. 또한, 스트리밍 서비스를 시작 할 때 사용자들이 일정시간 저화질의 비디오를 시청해야 하는 상황을 막는 시작 메커니즘(Start Mechanism)과 버퍼의 오버플로우를 방지하는 대기 메커니즘(Sleeping Mechanism)을 포함한다. 최종적으로 제안된 알고리즘이 FDASH에 비해 좋은 성능을 가짐을 NS-3를 이용한 모의실험을 통해 검증한다. 모의실험 결과, 제안된 방식이 FDASH에 비해 제한된 버퍼크기 상황 하에서도 버퍼 언더플로우/오버플로우가 발생하지 않음을 확인하였다. 또한 점대점(Point-to-Point) 환경과 Wi-Fi환경에서 거의 동일 화질 성능을 보이면서도 비디오 화질 변화 횟수를 50% 이상 줄일 수 있음을 확인하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권1호
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• pp.49-53
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• 2011

Path following of the mobile robot is one research hot for the mobile robot navigation. For the control system of the wheeled mobile robot(WMR) being in nonhonolomic system and the complex relations among the control parameters, it is difficult to solve the problem based on traditional mathematics model. In this paper, we presents a simple and effective way of implementing an adaptive following controller based on the PID for mobile robot path following. The method uses a non-linear model of mobile robot kinematics and thus allows an accurate prediction of the future trajectories. The proposed controller has a parallel structure that consists of PID controller with a fixed gain. The control law is constructed on the basis of Lyapunov stability theory. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity and orientation tracking control of the nonholonomic WMR. The simulation results of wheel type mobile robot platform are given to show the effectiveness of the proposed algorithm.

• 한국지능시스템학회논문지
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• 제14권6호
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• pp.752-758
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• 2004

본 논문에서는 고전적인 슬라이딩 모드 제어에서 단점으로 나타나는 채터링을 감소시키고 도달 시간을 줄이기 위한 적응 퍼지 슬라이딩 모드 제어기를 제안하였다. 전문가의 경험이나 직관에 주로 의존하는 제어 규칙의 획득을 쉽게 하기 위해 최대 경사법을 이용하여 슬라이딩 모드 조건이 만족되면서 채터링 현상을 줄이기 위한 제어 규칙의 결론부 파라미터를 수정하는 적응 알고리즘을 제안하였다. 제안된 알고리즘은 고전적인 가변 구조 제어 시스템의 장점인 외란, 매개변수 변화와 불확실성에 둔감한 성질을 그대로 간직하고 있다. 제안한 알고리즘의 유용성을 보이기 위해 도립 진자 시스템에 적용한 결과 채터링 감소와 빠른 응답 특성을 얻을 수 있다.