With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally...
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With applying the information technology to the military field, the advantages and importance of the networked combat are more and more obvious. In order to make full use of limited battlefield resources and maximally destroy enemy targets from arbitrary angle in a limited time, the research on firepower nodes dynamic deployment becomes a key problem of command and control. Considering a variety of tactical indexes and actual constraints in air defense, a mathematical model is formulated to minimize the enemy target penetration probability. Based on characteristics of the mathematical model and demands of the deployment problems, an assistance-based algorithm is put forward which combines the artificial potential field (APF) method with a memetic algorithm. The APF method is employed to solve the constraint handling problem and generate feasible solutions. The constrained optimization problem transforms into an optimization problem of APF parameters adjustment, and the dimension of the problem is reduced greatly. The dynamic deployment is accomplished by generation and refinement of feasible solutions. The simulation results show that the proposed algorithm is effective and feasible in dynamic situation.
After black-start(BS) generator restarts successfully during system restoration process, it is a primary task to provide cranking power to non-black-start(NBS) generators.A two-step optimal generator start-up sequence...
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After black-start(BS) generator restarts successfully during system restoration process, it is a primary task to provide cranking power to non-black-start(NBS) generators.A two-step optimal generator start-up sequence method for power system restoration is proposed in this *** step Ⅰ, the generator which is easiest to restart is selected as the first generator for safe *** step Ⅱ, a multi-objective optimization model which has a primary objective and two secondary objectives is built with consideration of the influence of restoration paths.A neighborhood is designed by the neighborhood search method to ensure the quality of solutions according to the solution of the primary ***-EDA is applied to search pareto optimal solutions in the designed *** results of a practical power system demonstrate the two-step method can take less time to determine several pareto optimal generator sequences and corresponding restoration paths and has potential to be used to guide restoration process in real time.
To ensure the reliable operation of power systems, adequate reserve capacity must be allocated properly. Considering transmission constraints, reserve capacity from various nodes has different effects on the system re...
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To ensure the reliable operation of power systems, adequate reserve capacity must be allocated properly. Considering transmission constraints, reserve capacity from various nodes has different effects on the system reliability. Spinning reserve is procured in this paper responding to the imbalance between load and generation, which influences system reliability level described by the value of lost load (VOLL). The reserve value is derived through VOLL. From the perspective of demand and supply equilibrium, a reasonable decision can be made for spinning reserve allocation at each node. Simulation results demonstrate the effectiveness of the proposed scheme.
In this paper, we use the coplanar multi-electrode for designing a rod-shaped sensor for measuring the ice thickness. In order to analyze and study mechanism and feasibility of ice thickness measurements using this te...
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<正>Enhancing the quantum efficiency of lanthanide-doped upconversion nanocrystals is crucial for applying them in fluorescence imaging,biosensing and optoelectronic applications[1,2].Here we demonstrate numerically...
<正>Enhancing the quantum efficiency of lanthanide-doped upconversion nanocrystals is crucial for applying them in fluorescence imaging,biosensing and optoelectronic applications[1,2].Here we demonstrate numerically that the upconversion luminescence based on excited state absorption can be improved by two
This paper presents a control strategy based on phase modification during double support period to enhance a humanoid robot's walking stability. When the foot of the swing leg touches the ground, if Zero Moment Po...
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ISBN:
(纸本)9781479973989
This paper presents a control strategy based on phase modification during double support period to enhance a humanoid robot's walking stability. When the foot of the swing leg touches the ground, if Zero Moment Point(ZMP) is not in the stable margin, the phase modification will start. According to the position of ZMP and the relationship between the motion of Center of Gravity(COG) and ZMP position, the related parameters are solved. Series of experiments are taken, and the effectiveness of the method is validated repeatedly.
An adaptive distributed differential evolution algorithm is proposed based on the change of the individual's fitness value. Firstly, the initial population is divided into several subpopulations. When the migratio...
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An adaptive distributed differential evolution algorithm is proposed based on the change of the individual's fitness value. Firstly, the initial population is divided into several subpopulations. When the migration condition is satisfied, the best individual in each subpopulation will replace the worst individual of its neighbor subpopulations according to the Von Neumann topology. The migration mechanism among subpopulations enables the information to be communicated in the whole population. Meanwhile, the adaptive mechanism of F and CR is presented for assigning different F and CR to each individual according to the individual's fitness. Numerical results show that, the proposed algorithm is beneficial to explore the solution space, which can avoid the premature convergence and search the excellent solutions.
A humanoid robot may suffer from slip since its two feet are not fixed on the ground. Slip occurrence may induce the loss of robot's balance. The previous literature focused on the detection or estimation of the s...
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A humanoid robot may suffer from slip since its two feet are not fixed on the ground. Slip occurrence may induce the loss of robot's balance. The previous literature focused on the detection or estimation of the slip occurrence, or only employed the translational acceleration regulation to overcome slip. This study proposes a slip prevention method by coordinating acceleration vector including the horizontal, vertical, and rotational acceleration components. The contribution of this paper is to regulate the translational and rotational acceleration together to prevent the slip occurrence. The effectiveness of our proposed method was verified by simulations and experiments on an actual humanoid robot.
An open architecture of power system numerical simulation software is proposed, the interface information between simulation engine and user program is exchanged by Client/Server implementation. The open application p...
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An open architecture of power system numerical simulation software is proposed, the interface information between simulation engine and user program is exchanged by Client/Server implementation. The open application program interface is realized by establishing an identical and standardized database(a normalized function interface table) on both sides so that they can understand each other through table searching. The client-side secondary development is not limited to single programming language. Interface software packages have been developed for different programming languages including C++, Matlab and Python. It is verified that the proposed framework has powerful openness as well as flexibility, which will greatly improve the calculating and analyzing capabilities of the power system numerical simulation software.
In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get parti...
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In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get partial measuring states information from its neighboring agent and obstacle. Coordinated obstacle avoidance here represents not only the agents moving without collision with an obstacle, but also the agents bypassing and assembling at the opposite side of the obstacle collectively, where the opposite side is defined according to the initial relative position of the agents to the obstacle. We focus on the collective obstacle avoidance algorithms for both agents with first-order kinematics and agents with second-order dynamics. In the situation where only a fixed fraction of agents can sense obstacle information for agents with first-order kinematics, we propose a collective obstacle avoidance algorithm without velocity measurements. And then we extend the algorithm to the case in switched topology. We show that all agents can bypass an obstacle and converge together, and then assemble at the opposite side of the obstacle in finite time, if the agents׳ topology graph is connected and at least one agent can sense the obstacle. In the case where obstacle information is available to only a fixed fraction of agents with second-order kinematics, we propose two collective obstacle avoidance algorithms without measuring acceleration when the obstacle has varying velocity and constant velocity. The switched topology is considered and extended next. We show that agents can bypass the obstacle with their positions and velocities approaching consensus in finite time if the connectivity of switched topology is continuously maintained. Several simulation examples demonstrate the proposed algorithms.
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