• International Journal of Control, Automation, and Systems
• /
• v.4 no.4
• /
• pp.428-437
• /
• 2006

Many physical systems are hybrid in the sense that they have continuous behaviors and discrete phenomena. In control system with multiple models, switching strategy and stability of the closed-loop system under switching are very important issues. In this paper, a novel adaptive control scheme based on multiple parameter models is proposed to cope with a change in Parameters. Switching strategy guarantees the non-increase in the global control Lyapunov function if the estimation of Lyapunov function value converges. Least-square estimation is used to find the estimated value of the Lyapunov function. Switching and adaptation law guarantees the stability of closed-loop system in the sense of Lyapunov. Simulation results on anti-lock brake system are shown to verify the effectiveness of the proposed controller in view of a large change in system parameters.

• Journal of Power System Engineering
• /
• v.18 no.5
• /
• pp.129-136
• /
• 2014

This paper proposes improvement on sensorless vector control performance of a permanent magnet synchronous motor (PMSM) with sliding mode observer. An adaptive observer gain and second order cascade low-pass filter (LPF) were used to improve the estimation accuracy of the rotor position and speed. The adaptive observer gain was applied to suppress the chattering intensity and obtained by using the Lyapunov's stability criterion. The second order cascade LPF was designed for the system to escalate the filtering performance of the back-emf estimation. Furthermore, genetic algorithm was used to optimize the system PI controller's performance. Simulation results showed the effectiveness of the suggested improvement strategy. Moreover, the strategy was useful for the sensorless vector control of PMSM to operate on the low-speed area.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.701-702
• /
• 2008

An adaptive response surface method with Latin Hypercube sampling strategy is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed algorithm consists of the multi-objective Pareto optimization and (1+${\lambda}$) evolution strategy to find the global optimal points with relatively fewer sampling data. In the adaptive RSM, an adaptive sampling point insertion method is developed utilizing the design sensitivities computed by using finite element method to get a reasonable response surface with a relatively small number of sampling points. The developed algorithm is applied to the shape optimization of PM poles for 6 MW BLDC motor, and the cogging torque is reduced to 19% of the initial one.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.9
• /
• pp.4375-4388
• /
• 2018

To solve the problem of transmission errors in stereoscopic images, this paper proposes a novel error concealment (EC) method using superpixel segmentation and adaptive disparity selection (SSADS). Our algorithm consists of two steps. The first step is disparity estimation for each pixel in a reference image. In this step, the numbers of superpixel segmentation labels of stereoscopic images are used as a new constraint for disparity matching to reduce the effect of mismatching. The second step is disparity selection for a lost block. In this step, a strategy based on boundary smoothness is proposed to adaptively select the optimal disparity which is used for error concealment. Experimental results demonstrate that compared with other methods, the proposed method has significant advantages in both objective and subjective quality assessment.

• Advances in Computational Design
• /
• v.1 no.3
• /
• pp.275-296
• /
• 2016

This article presents an adaptive directional differential evolution (ADDE) algorithm and its application in solving discrete sizing truss optimization problems. The algorithm is featured by a new self-adaptation approach and a simple directional strategy. In the adaptation approach, the mutation operator is adjusted in accordance with the change of population diversity, which can well balance between global exploration and local exploitation as well as locate the promising solutions. The directional strategy is based on the order relation between two difference solutions chosen for mutation and can bias the search direction for increasing the possibility of finding improved solutions. In addition, a new scaling factor is introduced as a vector of uniform random variables to maintain the diversity without crossover operation. Numerical results show that the optimal solutions of ADDE are as good as or better than those from some modern metaheuristics in the literature, while ADDE often uses fewer structural analyses.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2341-2344
• /
• 2001

In recent years the neural network known as a sort of the intelligent control strategy is used as a powerful tool for designing control system since it has learning ability. But it is difficult for neural network controllers to guarantee the stability of control systems. In this paper we try connecting a radial basis function network to an adaptive control strategy. Radial basis function networks are simpler and easier to handle than multilayer perceptrons. We use the radial basis function network to generate control input signals that are similar to the control inputs of adaptive control using linear reparameterization of the robot manipulator. We adopt the saturation function as an auxiliary controller. This paper also proves mathematically the stability of the control system under the existence of disturbances and modeling errors.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.5
• /
• pp.1544-1550
• /
• 2014

In this paper, an adaptive optimization strategy utilizing Kriging model and genetic algorithm is proposed for the optimal design of electromagnetic devices. The ordinary Kriging assisted by the spherical covariance model is used to construct surrogate models. In order to improve the computational efficiency, the adaptive uniform sampling strategy is applied to generate sampling points in design space. Through several iterations and gradual refinement process, the global optimal point can be found by genetic algorithm. The proposed algorithm is validated by application to the optimal design of a switched reluctance motor, where the stator pole face and shape of pole shoe attached to the lateral face of the rotor pole are optimized to reduce the torque ripple.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3295-3311
• /
• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.4
• /
• pp.522-533
• /
• 2012

This paper presents an adaptive strategy of GENCOs for reducing the greenhouse gas by fuel mix change. Fuel mix stands for generation capacity portfolio composed of different fuel resources. Currently, the generation sector of power industry in Korea is heavily dependent on fossil fuels, therefore it is required to change the fuel mix gradually into more eco-friendly way based on renewable energies. The generation costs of renewable energies are still expensive compared to fossil fueled resources. This is why the adaptive change is more preferred at current stage and this paper proposes an optimal strategy for capacity planning based on multiple environmental scenarios on the time horizon. This study used the computer program tool named GATE-PRO (Generation And Transmission Expansion PROgram), which is a mixed-integer non-linear program developed by Hongik university and Korea Energy Economics Institute. The simulations have been carried out with the priority allocation method in the program to determine the optimal mix of NRE(New Renewable Energy). Through this process, the result proposes an economic fuel mix under emission constraints compatible with the greenhouse gas mitigation policy of the United Nations.

• Journal of Power Electronics
• /
• v.17 no.6
• /
• pp.1469-1479
• /
• 2017

Primary-side regulation (PSR) scheme is widely applied in low power applications, such as cell phone chargers, network adapters, and LED drivers. However, the efficiency and standby power requirements have been improved to a high standard due to the new trends of DOE (Department Of Energy) Level VI and COC (Code Of Conduct specifications) V5. The major drawbacks of PSR include poor regulation due to inaccurate feedback and difficulty in acquiring acceptable regulation. A novel adaptive blanking strategy for constant current and constant voltage regulation is proposed in this paper. An accurate model for the sample blanking time related to transformer leakage inductance and the metal-oxide-semiconductor field-effect transistor (MOSFET) parasitic capacitance is established. The proposed strategy can achieve accurate detection for ultra-low standby power. In addition, numerous control factors are analyzed in detail to eliminate the influence of leakage inductance on the loop stability. A dedicated controller integrated circuit (IC) with a power MOSFET is fabricated to verify the effectiveness of the proposed control strategy. Experimental results demonstrated that the prototype based on the proposed IC has excellent performance.