• Nuclear Engineering and Technology
• /
• v.25 no.1
• /
• pp.110-124
• /
• 1993

A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.1
• /
• pp.69-74
• /
• 1999

Adaptive algorithms based on gradient adaptation have been extensively investigated and successfully joined with active noise/vibration control applications. The Filtered-X LMS algorithm became one of the basic feedforward algorithms in such applications, but is not fully understood yet. Effects of cancellation path model on the Filtered-X LMS algorithm have investigated and some useful properties related to stability were discovered. Most of the results stated that the error in the cancellation path model is undesirable to the Filtered X LMS. However, we started convergence analysis of Filtered-X LMS based on the assumption that erroneous model does not always degrade its performance. In this paper, we present a way of optimizing the cancellation path modern in order to enhance the convergence speed by introducing intentional phase error. Carefully designed intentional phase error enhances the convergence speed of the Filtered X LMS algorithm for pure tone noise suppression application without any performance loss at steady state.

• Journal of KSNVE
• /
• v.8 no.6
• /
• pp.1037-1042
• /
• 1998

This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. We also Propose a novel control algorithm (AFC/CAFC) for tonal noise cancellation. The proposed algorithm estimates the magnitude and phase of the tonal noise. The algorithm uses the steepest descent method for the phase/magnitude estimation. Performances of tile CAFC algorithm are presented in comparison with those by the AFC algorithm based on computer simulations and experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.54 no.4
• /
• pp.220-227
• /
• 2005

This paper presents hybrid artificial intelligent(HAI) controller based on the vector controlled IPMSM drive system. And it is based on artificial technologies that adaptive neural network fuzzy(A-NNF) is to speed control and artificial neural network(ANN) is to speed estimation. The salient feature of this technique is the HAI controller The hybrid action tolerates any inaccuracies in the fuzzy logic assignment rules or in the neural network stationary weights. Speed estimators using feedforward multilayer and artificial neural network(ANN) are compared. The back-propagation algorithm is easy to derived the estimated speed tracks precisely the actual motor speed. This paper presents the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.11b
• /
• pp.1132-1137
• /
• 2001

The smart foam that is first proposed by Fuller(2) is not applicable to active noise control in a duct having flow. Thus. this paper presents the ring-type smart foam as an alternative. The ring-type smart foam consists of polyurethane acoustic foam of lining shape and PVDF film embedded along the mid-surface of the foam lining. A feedforward adaptive filtered-x LMS controller is used to minimize the signal from the error microphone. To enlarge quiet sound region. two error microphones are used to update system modeling filter (SIMO method). Sound intensity control using the ring-type smart foam is also discussed

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2001.05a
• /
• pp.426-430
• /
• 2001

Conventional smart foam is not applicable to active noise control in a duct having flow. Thus, this paper presents a ring-type smart foam as an alternative. The ring-type smart foam consists of polyurethane acoustic foam of lining shape and PVDF film embedded in the foam. The embedded PVDF element acts as an actuator to reduce noise at lower frequencies and the foam absorbs noise at higher frequencies. A feedforward adaptive filtered-x LMS controller is used to minimize the signal from the error microphone. Experiments are executed to reduce broadband and tonal noise.

• Journal of Power Electronics
• /
• v.7 no.2
• /
• pp.159-173
• /
• 2007

In this paper, an intelligent sliding-mode position controller (ISMC) for achieving favorable decoupling control and high precision position tracking performance of permanent-magnet synchronous motor (PMSM) servo drives is proposed. The intelligent position controller consists of a sliding-mode position controller (SMC) in the position feed-back loop in addition to an on-line trained fuzzy-neural-network model-following controller (FNNMFC) in the feedforward loop. The intelligent position controller combines the merits of the SMC with robust characteristics and the FNNMFC with on-line learning ability for periodic command tracking of a PMSM servo drive. The theoretical analyses of the sliding-mode position controller are described with a second order switching surface (PID) which is insensitive to parameter uncertainties and external load disturbances. To realize high dynamic performance in disturbance rejection and tracking characteristics, an on-line trained FNNMFC is proposed. The connective weights and membership functions of the FNNMFC are trained on-line according to the model-following error between the outputs of the reference model and the PMSM servo drive system. The FNNMFC generates an adaptive control signal which is added to the SMC output to attain robust model-following characteristics under different operating conditions regardless of parameter uncertainties and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode position controller. The results confirm that the proposed ISMC grants robust performance and precise response to the reference model regardless of load disturbances and PMSM parameter uncertainties.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.3
• /
• pp.1265-1274
• /
• 2018

This paper proposes a virtual flux (VF) and positive-sequence power based control strategy to improve the performance of grid-interfaced three-phase voltage source converters against unbalanced and distorted grid conditions. By using a second-order generalized integrator (SOGI) based VF observer, the proposed strategy achieves an AC voltage sensorless and grid frequency adaptive control. Aiming to realize a balanced sinusoidal line current operation, the fundamental positive-sequence component based instantaneous power is utilized as the control variable. Moreover, the fundamental negative-sequence VF feedforward and the harmonic attenuation ability of a sequence component generator are employed to further enhance the unbalance regulation ability and the harmonic tolerance of line currents, respectively. Finally, the proposed scheme is completed by combining the foregoing two elements with a predictive direct power control (PDPC). In order to verify the feasibility and validity of the proposed SOGI-VFPDPC, the scenarios of unbalanced voltage dip, higher harmonic distortion and grid frequency deviation are investigated in simulation and experimental studies. The corresponding results demonstrate that the proposed strategy ensures a balanced sinusoidal line current operation with excellent steady-state and transient behaviors under general grid conditions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.545-546
• /
• 2012

일반적으로 회전력이 발생하는 제어시스템에 있어서 발생되는 외란과 시스템의 동특성에 의해 발생되는 리플 등을 보정하기 위해 다양한 제어기법들이 연구되고 있다. 특히, 제어시스템에 존재하는 미지의 외란을 제거하기 위하여 AFC(Adaptive Feedforward Cancellation) 제어이론을 적용하여 미지의 외란에 대한 시스템의 안정성을 확보하려고 노력하고 있다. 그러나 기존의 AFC의 구현을 위하여 연속 시간제어시스템의 전달함수인 IMP(Internal Model Principle)를 이용하여 특정 주파수 영역에 대한 외란을 제거하고 있지만 보다 광범위한 영역에 대해서는 제어 성능은 아직 부족한 편이다. 본 논문에서는 기존의 PID 제어기를 이용한 위치제어에 있어서 발생할 수 있는 외란을 제거하기 위해 AFC 제어이론인 IMP 전달함수와 인공지능 기법인 Fuzzy 제어기를 추가로 설계하여 모터의 위치제어에 대한 성능과 외란 제어에 대한 성능을 제시하고자 한다.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.39 no.4
• /
• pp.6-15
• /
• 2002

A neural network disturbance observer for a robotic manipulator is derived in this paper. The neural network used as the disturbance observer is a feedforward MLP(multiple-layered perceptron) network. The uniform ultimate boundness(UUB) of the proposed neural disturbance observer and the control error within a sufficiently small compact set is guaranteed. This neural disturbance observer method overcomes the disadvantages of the existing adaptive control methods which require the tedious analysis of the regressor matrix of the given manipulator. The effectiveness of the proposed neural disturbance observer is demonstrated by the application to the three-link robotic manipulator.