• Title/Summary/Keyword: Genetic stability

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Optimal Trajectory Generation for Biped Robots Walking Up-and-Down Stairs

  • Kwon O-Hung;Jeon Kweon-Soo;Park Jong-Hyeon
    • Journal of Mechanical Science and Technology
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    • v.20 no.5
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    • pp.612-620
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    • 2006
  • This paper proposes an optimal trajectory generation method for biped robots for walking up-and-down stairs using a Real-Coded Genetic Algorithm (RCGA). The RCGA is most effective in minimizing the total consumption energy of a multi-dof biped robot. Each joint angle trajectory is defined as a 4-th order polynomial of which the coefficients are chromosomes or design variables to approximate the walking gait. Constraints are divided into equalities and inequalities. First, equality constraints consist of initial conditions and repeatability conditions with respect to each joint angle and angular velocity at the start and end of a stride period. Next, inequality constraints include collision prevention conditions of a swing leg, singular prevention conditions, and stability conditions. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot model that consists of seven links in the sagittal plane. The optimal trajectory is more efficient than that generated by the Modified Gravity-Compensated Inverted Pendulum Mode (MGCIPM). And various trajectories generated by the proposed GA method are analyzed from the viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

Multi-Level Thresholding based on Non-Parametric Approaches for Fast Segmentation

  • Cho, Sung Ho;Duy, Hoang Thai;Han, Jae Woong;Hwang, Heon
    • Journal of Biosystems Engineering
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    • v.38 no.2
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    • pp.149-162
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    • 2013
  • Purpose: In image segmentation via thresholding, Otsu and Kapur methods have been widely used because of their effectiveness and robustness. However, computational complexity of these methods grows exponentially as the number of thresholds increases due to the exhaustive search characteristics. Methods: Particle swarm optimization (PSO) and genetic algorithms (GAs) can accelerate the computation. Both methods, however, also have some drawbacks including slow convergence and ease of being trapped in a local optimum instead of a global optimum. To overcome these difficulties, we proposed two new multi-level thresholding methods based on Bacteria Foraging PSO (BFPSO) and real-coded GA algorithms for fast segmentation. Results: The results from BFPSO and real-coded GA methods were compared with each other and also compared with the results obtained from the Otsu and Kapur methods. Conclusions: The proposed methods were computationally efficient and showed the excellent accuracy and stability. Results of the proposed methods were demonstrated using four real images.

Design of Fuzzy Power System Stabilizer using Real-coding Genetic Algorithm (실수형 유전알고리즘을 이용한 전력계통 퍼지안정화장치의 설계)

  • Lee, Jong-Kyu;Kwon, Soon-Il;Kim, Sung-Shin;Park, June-Ho;Hwang, Gi-Hyun
    • Proceedings of the KIEE Conference
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    • 2001.07a
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    • pp.134-136
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    • 2001
  • This paper describes the application of Fuzzy Power System Stabilizer(FPSS) for improving dynamic stability of power system. The Real-coding Genetic Algorithm(RGA) was applied to optimize gains of the inputs and outputs of the FPSS. The effectiveness of the proposed FPSS was demonstrated by simulation studies for single-machine infinite system. To show the superiority of the proposed FPSS, its performances were compared with those of Conventional Power System Stabilizer(CPSS) The proposed FPSS showed better control performances than the CPSS in three-phase ground fault under a normal load which was system condition in tuning FPSS. To show the robustness of the proposed FPSS, it was applied to damp the low frequency oscillations caused by disturbances such as three-phase ground fault under heavy and light load conditions. The proposed FPSS showed better performance than CPSS in terms of the settling time and damping effect for power system operation condition.

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Optimization of Dynamic Neural Networks for Nonlinear System control (비선형 시스템 제어를 위한 동적 신경망의 최적화)

  • Ryoo, Dong-Wan;Lee, Jin-Ha;Lee, Young-Seog;Seo, Bo-Hyeok
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.740-743
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    • 1998
  • This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.

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A Study on the Optimal Setting Method of Directional Overcurrent Relay Considering Fault Ride Through of Distributed Generation (분산전원의 Fault Ride Through를 고려한 방향성 과전류 계전기 최적 정정법에 관한 연구)

  • Song, Jin-Sol;Cho, Gyu-Jung;Kim, Ji-Soo;Shin, Jea-Yun;Kim, Dong-Hyun;Kim, Chul-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.8
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    • pp.1002-1008
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    • 2018
  • Fault Ride Through(FRT) requirement prevents disconnections of distributed generations during the specific time on disturbance condition for system stability. However, since there is a limitation to the FRT capability of distributed generation, and the protection system needs to clear the fault quickly before the distributed generation is disconnected. Therefore, this paper proposes a novel optimal setting method of directional overcurrent relay considering FRT of distributed generation. The proposed method reduces the probability of disconnections of the distributed generation in disturbance without additional equipment considering the FRT capability of the distributed generation by calculating the optimal relay setting through the Genetic Algorithm(GA).

Poly(ADP-ribosyl)ation of p53 Contributes to TPEN-Induced Neuronal Apoptosis

  • Kim, Hyun-Lim;Ra, Hana;Kim, Ki-Ryeong;Lee, Jeong-Min;Im, Hana;Kim, Yang-Hee
    • Molecules and Cells
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    • v.38 no.4
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    • pp.312-317
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    • 2015
  • Depletion of intracellular zinc by N,N,N,N-tetrakis(2-pyridylmethyl) ethylenediamine (TPEN) induces p53-mediated protein synthesis-dependent apoptosis of mouse cortical neurons. Here, we examined the requirement for poly(ADP-ribose) polymerase (PARP)-1 as an upstream regulator of p53 in zinc depletion-induced neuronal apoptosis. First, we found that chemical inhibition or genetic deletion of PARP-1 markedly attenuated TPEN-induced apoptosis of cultured mouse cortical neurons. Poly(ADP-ribosyl)ation of p53 occurred starting 1 h after TPEN treatment. Suggesting the critical role of PARP-1, the TPEN-induced increase of stability and activity of p53 as well as poly(ADP-ribosyl)ation of p53 was almost completely blocked by PARP inhibition. Consistent with this, the induction of downstream pro-apoptotic proteins PUMA and NOXA was noticeably reduced by chemical inhibitors or genetic deletion of PARP-1. TPEN-induced cytochrome C release into the cytosol and caspase-3 activation were also blocked by inhibition of PARP-1. Taken together, these findings indicate that PARP-1 is essential for TPEN-induced neuronal apoptosis.

UPFC Device: Optimal Location and Parameter Setting to Reduce Losses in Electric-Power Systems Using a Genetic-algorithm Method

  • Mezaache, Mohamed;Chikhi, Khaled;Fetha, Cherif
    • Transactions on Electrical and Electronic Materials
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    • v.17 no.1
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    • pp.1-6
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    • 2016
  • Ensuring the secure operation of power systems has become an important and critical matter during the present time, along with the development of large, complex and load-increasing systems. Security constraints such as the thermal limits of transmission lines and bus-voltage limits must be satisfied under all of a system’s operational conditions. An alternative solution to improve the security of a power system is the employment of Flexible Alternating-Current Transmission Systems (FACTS). FACTS devices can reduce the flows of heavily loaded lines, maintain the bus voltages at desired levels, and improve the stability of a power network. The Unified Power Flow Controller (UPFC) is a versatile FACTS device that can independently or simultaneously control the active power, the reactive power and the bus voltage; however, to achieve such functionality, it is very important to determine the optimal location of the UPFC device, with the appropriate parameter setting, in the power system. In this paper, a genetic algorithm (GA) method is applied to determine the optimal location of the UPFC device in a network for the enhancement of the power-system loadability and the minimization of the active power loss in the transmission line. To verify our approach, simulations were performed on the IEEE 14 Bus, 30 Bus, and 57 Bus test systems. The proposed work was implemented in the MATLAB platform.

An improved Loop Shaping Approach of QFT using Genetic Algorithm and a Design of Steam Generator Water Level Control System in Nuclear Power Station (유전 알고리듬을 이용한 개선된 QFT의 루프 형성법 및 원전 증기발생기 수위제어계의 설계)

  • 김주식;김민환;유정웅
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.12 no.4
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    • pp.106-113
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    • 1998
  • The steam generator waste level control system in a nuclear power station has difficulty in its mathematical modeling and theoretical application in both a transient and steady state operation. Therefore, the stability problem of the conventional control methods brings many researches interests to the various methods of a system design in recent years. In this study, an improved loop shaping approach is proposed by applying the genetic algorithm to QFT (Quantitative Feedback Theory) in designing a control system in order to the performance of the system. And the effects of the proposed methods are shown by the simulation results.

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Oligomeric Structure of ${\beta}$-Glucosidases

  • Kim, Sang-Yeob;Kimm, In-Soo
    • Journal of Photoscience
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    • v.11 no.3
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    • pp.121-127
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    • 2004
  • The${\beta}$-glucosidases occur widely in all living organisms and has in general a tendency to form oligomers of varying numbers of subunits or aggregates, although the functional implications of such diverse oligomerization schemes remain unclear. In particular, the assembly mode of the oat ${\beta}$-glucosidase is very unique in that it multimerizes by linear stacking of a hexameric building block to form long fibrillar multimers. Some structural proteins such as actin and tubulin assemble into long fibrils in a helical fashion and several enzymes such as GroEL and Pyrodictium ATPase functional complexes, 20S proteasome of the archaebacterium Thermoplasma acidophilum, and lutamine synthetase fromblue-green algae, assemble into discrete oligomers upto 4 stacked rings to maintain their enzymatic activities. In particular, oat ${\beta}$-glucosidase exists in vivo as a discrete long fibrillar multimer assembly that is a novel structure for enzyme protein. It is assembled by linear stacking of hollow trimeric units. The fibril has a long central tunnel connecting to the outer medium via regularly distributed side fenestrations. The enzyme active sites are located within the central tunnel and multimerization increases enzyme affinity to the substrates and catalytic efficiency of the enzyme. Although it is suggested that oligomerization may contribute to the enzyme stability and catalytic efficiency of ${\beta}$-glycosidases, the functional implications of such diverse oligomerization schemes remain unclear so far.

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A Study on the Optimization Design of Damper for the Improvement of Vehicle Suspension Performance (차량 현가장치 성능향상을 위한 댐퍼 최적화 설계에 대한 연구)

  • Lee, Choon Tae
    • Journal of Drive and Control
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    • v.15 no.4
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    • pp.74-80
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    • 2018
  • A damper is a hydraulic device designed to absorb or eliminate shock impulses which is acting on the sprung mass of vehicle. It converting the kinetic energy of the shock into another form of energy, typically heat. In a vehicle, a damper reduce vibration of car, leading to improved ride comfort and running stability. Therefore, a damper is one of the most important components in a vehicle suspension system. Conventionally, the design process of vehicle suspensions has been based on trial and error approaches, where designers iteratively change the values of the design variables and reanalyze the system until acceptable design criteria are achieved. Therefore, the ability to tune a damper properly without trial and error is of great interest in suspension system design to reduce time and effort. For this reason, a many previous researches have been done on modeling and simulation of the damper. In this paper, we have conducted optimal design process to find optimal design parameters of damping force which minimize a acceleration of sprung mass for a given suspension system using genetic algorithm.