• Title/Summary/Keyword: Minimize Energy Inequality

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Energy Optimization of a Biped Robot for Walking a Staircase Using Genetic Algorithms

  • Jeon, Kweon-Soo;Park, Jong-Hyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.215-219
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    • 2003
  • In this paper, we generate a trajectory minimized the energy gait of a biped robot for walking a staircase using genetic algorithms and apply to the computed torque controller for the stable dynamic biped locomotion. In the saggital plane, a 6 degree of freedom biped robot that model consists of seven links is used. In order to minimize the total energy efficiency, the Real-Coded Genetic Algorithm (RCGA) is used. Operators of genetic algorithms are composed of a reproduction, crossover and mutation. In order to approximate the walking gait, the each joint angle is defined as a 4-th order polynomial of which coefficients are chromosomes. Constraints are divided into equality and inequality. Firstly, equality constraints consist of position conditions at the end of stride period and each joint angle and angular velocity condition for periodic walking. On the other hand, inequality constraints include the knee joint conditions, the zero moment point conditions for the x-direction and the tip conditions of swing leg during the period of a stride for walking a staircase.

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Balanced Cluster-based Multi-hop Routing in Sensor Networks (센서 네트워크의 균등분포 클러스터 기반 멀티홉 라우팅)

  • Wu, Mary
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.910-917
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    • 2016
  • Sensors have limited resources in sensor networks, so efficient use of energy is important. Representative clustering methods, LEACH, LEACHC, TEEN generally use direct transmission methods from cluster headers to the sink node to pass collected data. However, the communication distance of the sensor nodes at low cost and at low power is not long, it requires a data transfer through the multi-hop to transmit data to the sink node. In the existing cluster-based sensor network studies, cluster process and route selection process are performed separately in order to configure the routing path to the sink node. In this paper, in order to use the energy of the sensor nodes that have limited resources efficiently, a cluster-based multi-hop routing protocol which merges the clustering process and routing process is proposed. And the proposed method complements the problem of uneven cluster creation that may occur in probabilistic cluster methods and increases the energy efficiency of whole sensor nodes.

Real Coded Biogeography-Based Optimization for Environmental Constrained Dynamic Optimal Power Flow

  • Kumar, A. Ramesh;Premalatha, L.
    • Journal of Electrical Engineering and Technology
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    • v.10 no.1
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    • pp.56-63
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    • 2015
  • The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.

Trajectory Optimization for Biped Robots Walking Up-and-Down Stairs based on Genetic Algorithms (유전자 알고리즘을 이용한 이족보행 로봇의 계단 보행)

  • Jeon Kweon-Soo;Kwon O-Hung;Park Jong-Hyeon
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.4 s.181
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    • pp.75-82
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    • 2006
  • In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

Energy-Efficient Resource Allocation for Application Including Dependent Tasks in Mobile Edge Computing

  • Li, Yang;Xu, Gaochao;Ge, Jiaqi;Liu, Peng;Fu, Xiaodong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.6
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    • pp.2422-2443
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    • 2020
  • This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.