• Title/Summary/Keyword: optimization scheme

Search Result 1,157, Processing Time 0.036 seconds

A Biomechanical Model of Lower Extremity Movement in Seated Foot Operation

  • Kyu-Sung Hwang
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.23 no.60
    • /
    • pp.37-46
    • /
    • 2000
  • A biomechanical model of lower extremity in seated postures was developed to assess muscular activities of lower extremity involved in a variety of foot pedal operations. The model incorporated four rigid body segments with the twenty-four muscles to represent lower extremity This study deals with quasi-static movement to investigate dynamic movement effect in seated foot operation. It is found that optimization method which has been used for modeling the articulated body segments does not predict the forces generated from biarticular muscles and antagonistic muscles reasonably. So, the revised nonlinear optimization scheme was employed to consider the synergistic effects of biarticular muscles and the antagonistic muscle effects from the stabilization of the joint. For the model validation, three male subjects performed the experiments in which EMG activities of the nine lower extremity muscles were measured. Predicted muscle forces were compared with the corresponding EMG amplitudes and it showed no statistical difference. For the selection of optimal seated posture, a physiological meaningful criterion was developed for muscular load sharing developed. For exertion levels, the transition point of type F motor unit of each muscle is inferred by analyzing the electromyogram at the seated postures. Also, for predetermined seated foot operations exertion levels, the recruitment pattern is identified in the continuous exertion, by analyzing the electromyogram changes due to the accumulated muscle fatigue.

  • PDF

Augmentation of Fractional-Order PI Controller with Nonlinear Error-Modulator for Enhancing Robustness of DC-DC Boost Converters

  • Saleem, Omer;Rizwan, Mohsin;Khizar, Ahmad;Ahmad, Muaaz
    • Journal of Power Electronics
    • /
    • v.19 no.4
    • /
    • pp.835-845
    • /
    • 2019
  • This paper presents a robust-optimal control strategy to improve the output-voltage error-tracking and control capability of a DC-DC boost converter. The proposed strategy employs an optimized Fractional-order Proportional-Integral (FoPI) controller that serves to eliminate oscillations, overshoots, undershoots and steady-state fluctuations. In order to significantly improve the error convergence-rate during a transient response, the FoPI controller is augmented with a pre-stage nonlinear error-modulator. The modulator combines the variations in the error and error-derivative via the signed-distance method. Then it feeds the aggregated-signal to a smooth sigmoidal control surface constituting an optimized hyperbolic secant function. The error-derivative is evaluated by measuring the output-capacitor current in order to compensate the hysteresis effect rendered by the parasitic impedances. The resulting modulated-signal is fed to the FoPI controller. The fixed controller parameters are meta-heuristically selected via a Particle-Swarm-Optimization (PSO) algorithm. The proposed control scheme exhibits rapid transits with improved damping in its response which aids in efficiently rejecting external disturbances such as load-transients and input-fluctuations. The superior robustness and time-optimality of the proposed control strategy is validated via experimental results.

Research on UAV access deployment algorithm based on improved virtual force model

  • Zhang, Shuchang;Wu, Duanpo;Jiang, Lurong;Jin, Xinyu;Cen, Shuwei
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.16 no.8
    • /
    • pp.2606-2626
    • /
    • 2022
  • In this paper, a unmanned aerial vehicle (UAV) access deployment algorithm is proposed, which is based on an improved virtual force model to solve the poor coverage quality of UAVs caused by limited number of UAVs and random mobility of users in the deployment process of UAV base station. First, the UAV-adapted Harris Hawks optimization (U-AHHO) algorithm is proposed to maximize the coverage of users in a given hotspot. Then, a virtual force improvement model based on user perception (UP-VFIM) is constructed to sense the mobile trend of mobile users. Finally, a UAV motion algorithm based on multi-virtual force sharing (U-MVFS) is proposed to improve the ability of UAVs to perceive the moving trend of user equipments (UEs). The UAV independently controls its movement and provides follow-up services for mobile UEs in the hotspot by computing the virtual force it receives over a specific period. Simulation results show that compared with the greedy-grid algorithm with different spacing, the average service rate of UEs of the U-AHHO algorithm is increased by 2.6% to 35.3% on average. Compared with the baseline scheme, using UP-VFIM and U-MVFS algorithms at the same time increases the average of 34.5% to 67.9% and 9.82% to 43.62% under different UE numbers and moving speeds, respectively.

A Study on Shape Optimization of Distributed Actuators using Time Domain Finite Element Method (시간유한요소법을 이용한 분포형 구동기의 형상최적화에 관한 연구)

  • Suk, Jin-Young;Kim, You-Dan
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.33 no.9
    • /
    • pp.56-65
    • /
    • 2005
  • A dynamic analysis method that freezes a time domain by discretization and solves the spatial propagation equation has a unique feature that provides a degree of freedom on spatial domain compared with the space discretization or space-time discretization finite element method. Using this feature, the time finite element analysis can be effectively applied to optimize the spatial characteristics of distributed type actuators. In this research, the time domain finite element method was used to discretize the model. A state variable vector was used in the discretization to include arbitrary initial conditions. A performance index was proposed on spatial domain to consider both potential and vibrational energy, so that the resulting shape of the distributed actuator was optimized for dynamic control of the structure. It is assumed that the structure satisfies the final rest condition using the realizable control scheme although the initial disturbance can affect the system response. Both equations on states and costates were derived based on the selected performance index and structural model. Ricatti matrix differential equations on state and costate variables were derived by the reconfiguration of the sub-matrices and application of time/space boundary conditions, and finally optimal actuator distribution was obtained. Numerical simulation results validated the proposed actuator shape optimization scheme.

Study on Optimization of Blast Design for Improving Fragmentation in Jeju Basalt Rock Area (제주도 현무암에서 파쇄도 향상을 위한 최적 발파 설계 연구)

  • Yang, Hyung-Sik;Kim, Nam-Soo;Jang, Hyong-Doo;Kim, Won-Beom;Ko, Young-Hun;Kim, Seung-Jun;Kim, Jeong-Gyu;Moon, Hee-Sook
    • Explosives and Blasting
    • /
    • v.29 no.2
    • /
    • pp.89-99
    • /
    • 2011
  • Recently on Jeju island there has been a lot of development and construction. However random distribution of porous basalt and clinker seam generated from volcanic activities often interrupt and greatly reduce efficiency of blasting necessary for construction. Three test blasts were operated to solve the inefficiency problem and results indicated that a powder factor of 0.40~0.45 $kg/cm^3$ is necessary to increase the efficiency of blasting. Also the blasting scheme should be concerned whether clinker seams exists in excavation levels or not.

Second Order Suboptimal Power Allocation for MIMO-OFDM Based Cognitive Radio Systems

  • Nguyen, Tien Hoa;Nguyen, Thanh Hieu;Nguyen, Van Duc;Ha, Duyen Trung;Gelle, Guilllaume;Choo, Hyunseung
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.8 no.8
    • /
    • pp.2647-2662
    • /
    • 2014
  • This paper proposes an efficient and low complexity power-loading algorithm for MIMO-OFDM downlink based cognitive radio system that maximizes the sum rate of single secondary user (SU) under constraints on the tolerable interference thresholds between secondary user and primary user's frequency bands and the total transmission power. Our suboptimal algorithm is based on the $2^{nd}$ order interference tracking and nulling mechanism to allocate transmission power of the subcarriers among SU's scheme. The performance of our proposed suboptimal scheme is compared with the performance of the classical power loading algorithms, e.g., water filling, $1^{st}$ order interference tracking, nulling, and other suboptimal schemes. Numerical results show that our algorithm has low complexity but obtains a higher channel capacity than that of some previous suboptimal algorithms in some scenarios. We dedicate also that for a given interference threshold, the $2^{nd}$ order interference tracking mechanism has dynamic number of nulling position instead fixed number of nulling position.

Energy-Efficient Scheduling with Individual Packet Delay Constraints and Non-Ideal Circuit Power

  • Yinghao, Jin;Jie, Xu;Ling, Qiu
    • Journal of Communications and Networks
    • /
    • v.16 no.1
    • /
    • pp.36-44
    • /
    • 2014
  • Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

Resource allocation in downlink SWIPT-based cooperative NOMA systems

  • Wang, Longqi;Xu, Ding
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.14 no.1
    • /
    • pp.20-39
    • /
    • 2020
  • This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.

Hybrid Learning Architectures for Advanced Data Mining:An Application to Binary Classification for Fraud Management (개선된 데이터마이닝을 위한 혼합 학습구조의 제시)

  • Kim, Steven H.;Shin, Sung-Woo
    • Journal of Information Technology Application
    • /
    • v.1
    • /
    • pp.173-211
    • /
    • 1999
  • The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

  • PDF

High Luminous Efficiency Flat Light Source with Xe mixture Gas Discharge and Areal Brightness Control Method (제논 혼합가스를 이용한 고효율 면광원과 국부적 밝기 제어 방식)

  • Jung, Jae-Chul;Seo, In-Woo;Oh, Byung-Joo;Whang, Ki-Woong
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
    • /
    • 2009.10a
    • /
    • pp.153-157
    • /
    • 2009
  • A Highly efficient Mercury-free Flat Fluorescent Lamp (MFFL) with dielectric barrier Xe gas discharge was developed for an alternative of conventional line-type Cold Cathode Fluorescent Lamps (CCFLs) which shows a wide voltage margin and a stable discharge operation for diffuse glow discharge with an application of a auxiliary electrode. Electro-optic characteristics of the MFFL were examined through the changes in ambient temperature, total pressure and Xe partial pressure. the single cell is expanded into a multi-structured configuration to realize a large sized lamp by a simple repetition of the single cells, and a new driving scheme is proposed for an adaptive brightness control using dual auxiliary electrodes and bi-polar drive scheme. In addition, interesting application of this ultra high luminance flat lamp by the optimization of the gas condition and the pattern of the rear phosphor layer is suggested as a good alternative of daylight lamp source

  • PDF