• 한국조명전기설비학회:학술대회논문집
• /
• 한국조명전기설비학회 2009년도 추계학술대회 논문집
• /
• pp.355-358
• /
• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Welding and Joining
• /
• 제17권5호
• /
• pp.40-46
• /
• 1999

The sensors employed in the robotic are welding system must detect the changes in weld characteristics and produce the output that is in some way related to the change being detected. Such adaptive systems, which synchronise the robot arm and eyes using a primitive brain will form the basis for the development of robotic GMA(Gas Metal Arc) welding which increasingly higher levels of artificial intelligence. The objective of this paper is to realize the mapping characteristics of bead height through learning. After learning, the neural estimation can estimate the bead height desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) are chosen from an estimation error analysis. A series of bead of bead-on-plate GMA welding experiments was carried out in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the bead height with reasonable accuracy and guarantee the uniform weld quality.

• 한국자동차공학회논문집
• /
• 제10권5호
• /
• pp.190-198
• /
• 2002

Full scale durability test in the laboratory is an essential of any fatigue life evaluation of components or structures of the automotive vehicle. Component testing is particularly important in today's highly competitive industries where the design to reduce weight and production costs must be balanced with the necessity to avoid expensive service failure. Generally, hydraulic road simulator is used to carry out the fatigue test and the vibration test. In this paper, the algorithm and software to realize the real road profile are developed. The operation software for simultaneously controlled multi-axial road simulator is developed and the input and output data are displayed window based PC controller in the real time. Futhermore, the software to generate the real road profile are developed. The validity of the software are verified by applying the belgian road, the city road, the highway, and the gravel road. The results of the above experiment show that the real road profiles are realized well after 10th iteration.

• Journal of Information Processing Systems
• /
• 제19권2호
• /
• pp.149-163
• /
• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.

• 전기학회논문지P
• /
• 제56권2호
• /
• pp.74-82
• /
• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning control fuzzy neural network (AFLC-FNN) controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC-FNN controller. Also, this paper proposes speed control of IPMSM using AFLC-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled AFLC-FNN controller, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Industrial Engineering and Management Systems
• /
• 제8권4호
• /
• pp.239-246
• /
• 2009

This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.

• 전기학회논문지
• /
• 제62권10호
• /
• pp.1487-1493
• /
• 2013

A new simple control method for active power filter, which can realize the complete compensation of harmonics is proposed. In the proposed scheme, a model-based digital current control strategy is presented. The proposed control system is designed and implemented in a form referred to as internal model control structure. This method provides a convenient way for parameterizing the controller in term of the nominal system model, including time-delays. As a result, the resulting controller parameters are directly set based on the power circuit parameters, which make tuning of the controllers straightforward task. In the proposed control algorithm, overshoots and oscillations due to the computation time delay is prevented by explicit incorporating of the delay in the controller transfer function. In addition, a new compensating current reference generator employing resonance model implemented by a DSP(Digital Signal Processor) is introduced. Resonance model has an infinite gain at resonant frequency, and it exhibits a band-pass filter. Consequently, the difference between the instantaneous load current and the output of this model is the current reference signal for the harmonic compensation.

• 전자공학회논문지B
• /
• 제29B권11호
• /
• pp.120-129
• /
• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• Smart Structures and Systems
• /
• 제16권6호
• /
• pp.1023-1047
• /
• 2015

In this study, the optimal location of the MR fluid segments in a partially treated laminated composite sandwich plate has been identified to maximize the natural frequencies and the loss factors. The finite element formulation is used to derive the governing differential equations of motion for a partially treated laminated composite sandwich plate embedded with MR fluid and rubber material as the core layer and laminated composite plate as the face layers. An optimization problem is formulated and solved by combining finite element analysis (FEA) and genetic algorithm (GA) to obtain the optimal locations to yield maximum natural frequency and loss factor corresponding to first five modes of flexural vibration of the sandwich plate with various combinations of weighting factors under various boundary conditions. The proposed methodology is validated by comparing the natural frequencies evaluated at optimal locations of MR fluid pockets identified through GA coupled with FEA and the experimental measurements. The converged results suggest that the optimal location of MR fluid pockets is strongly influenced not only by the boundary conditions and modes of vibrations but also by the objectives of maximization of natural frequency and loss factors either individually or combined. The optimal layout could be useful to apply the MR fluid pockets at critical components of large structure to realize more efficient and compact vibration control mechanism with variable damping.

• 한국생산제조학회지
• /
• 제18권3호
• /
• pp.248-254
• /
• 2009

The worn crater wear geometry of coated tools after machining has been configured by using Confocal Laser Scanning Microscopy(CLSM) and the Wavelet-based filtering technique. The CLSM can be well suited to construct the three-dimensional crater wear on the rake surfaces of coated tips. However, The raw heightness data of HEI(height encoded image) acquired by CLSM must be filtered due to the electronic and imaging noise occurring in constructing the crater image. So the Wavelet-based filtering algorithm is necessary to denoise the shape features in a micro scales so as to realize accurate crater wear topography analysis. The crater wear patterns filtered enable us to predict the crater wear shape in order to study the tool wear evolution. The study shows that the technique by combining the CLSM and Wavelet-based filtering is an excellent one to obtain the geometries of worn tool rake surfaces over a wide range of surface resolution in a micro scale.