Robust Near-Hovering Flight Controller for Model-Scale Helicopters Via Parametric Approach

This paper aims to provide a parametric design for robust flight controller of the model-scale helicopter. The main contributions lie in two aspects. Firstly, under near-hovering condition, a procedure is presented for simplification of the highly nonlinear and under-actuated model of the model-scale helicopter. This nonlinear system is linearized around the trim values of the chosen flight mode, followed by decomposing this high-order linear model into three lower-order subsystems according to the coupling properties among channels. After decomposition, the three subsystems are obtained which include the coupling subsystem between the roll (pitch) motion and the lateral (longitudinal) motion, the subsystem of the yaw motion and the subsystem of the vertical motion. Secondly, by using eigenstructure assignment, the problem of flight controller design can be converted into solving two optimization problems and the linear robust controllers of these subsystems are designed through solving these optimization problems. Besides, this paper contrasts and analyzed the performances of the LQR controller and the parametric controller. The results demonstrate the effectiveness and the robustness against the parametric perturbations of the parametric controller.     

基于动态参数的按需可扩展地址分配算法

提出了一种基于动态参数的按需可扩展地址分配算法,根据分布式地址分配机制(DAAM)对16 bit地址空间进行分块,根据网络状况来动态调整参数以及进行地址一次或者多次扩展;同时改进路由算法,使其与Cluster-Tree协议兼容。仿真表明改进算法在地址分配成功率、平均分配耗时等方面优于DAAM以及它的改进方案EDAA-BA和RBAC。     

多个水下机器人动态任务分配和路径规划的信度自组织算法

针对多个水下机器人(autonomous underwater vehicles,AUVs)动态任务分配和路径规划速度跳变问题,引入栅格信度函数概念,给出一种改进的栅格信度自组织(belief function self-organizing map,BFSOM)算法.目的是控制一组AUV有效地到达所有指定的目标位置,同时保证AUV能够自动的避开障碍物.首先,自组织神经网络(self-organizing map,SOM)算法对多AUV系统进行任务分配,使得每个目标位置都有一个AUV去访问.整个分配过程包括定义SOM神经网络的初始权值、获胜者选择、邻域函数的计算3个步骤;其次,根据栅格信度函数和环境信息更新SOM获胜神经元的权值,使得每个AUV在访问对应目标的过程中能够自动避障并且克服速度跳变,实现AUV自动有效路径规划.最后,通过仿真实验证明了本文提及算法的有效性.     

高效动态存储再分配方案与实现

为提高大小和数量都不确定的数据动态存储的空间利用率和处理速度,针对常规系统动态存储分配存在的问题,提出一种高效的动态存储再分配方案。通过减少系统动态存储分配的执行次数,在有效提高存储空间利用率的同时,提高存储空间动态分配的速度,给出动态存储再分配方案的具体实现算法,用实际数据对其性能进行测试。测试结果表明,该方案能节省36％至75％的系统存储空间,分配速度提高了20至50倍。     

Evolutionary algorithm with a directional local search for multiobjective optimization in combinatorial problems

Evolutionary algorithms (EAs) are often employed to multiobjective optimization, because they process an entire population of solutions which can be used as an approximation of the Pareto front of the tackled problem. It is a common practice to couple local search with evolutionary algorithms, especially in the context of combinatorial optimization. In this paper a new local search method is proposed that utilizes the knowledge concerning promising search directions. The proposed method can be used as a general framework and combined with many methods of iterating over a neighbourhood of an initial solution as well as various decomposition approaches. In the experiments the proposed local search method was used with an EA and tested on 2-, 3- and 4-objective versions of two well-known combinatorial optimization problems: the travelling salesman problem (TSP) and the quadratic assignment problem (QAP). For comparison two well-known local search methods, one based on Pareto dominance and the other based on decomposition, were used with the same EA. The results show that the EA coupled with the directional local search yields better results than the same EA coupled with any of the two reference methods on both the TSP and QAP problems.     

基于IGHS算法的分段系统鲁棒极点配置优化

针对分段线性控制系统鲁棒极点配置问题,利用IGHS算法对特征向量矩阵条件数优化具有较好的收敛性,限制了特征向量选择的自由度.优化后的控制器使闭环系统矩阵允许有更大的摄动或不确定性.与已有方法相比,本文方法对条件数优化计算既不需要考虑梯度和二次可微信息,也不需要对条件数进行凸转化处理.最后,仿真实验结果验证了本方法的有效性.     

Uplink resource allocation in OFDMA system using distributed antennas

In this article, we investigate uplink resource allocation in orthogonal frequency division multiple access （OFDMA） systems that use distributed antennas. The multiple distributed receiving antennas motivate us to exploit the spatial diversity to maximize the achievable rate of the system. Given constraints on the subcarrier allocation and the power limit of each user equipment （UE）, a mixed-integer optimization problem is formulated. We first propose a centralized greedy algorithm to find the maximum achievable rate of the system. Then a heuristic algorithm is proposed that can be implemented in a distributed manner. Simulation results show that the heuristic algorithm can approximately achieve the maximum achievable rate of the system and result in significant system performance improvement over the approach assigning one user to each subcarrier.     

利用特征点序列截断的图像匹配判决算法

当图像中特征点缺失比较严重时,利用特征点S维分配算法和K均值聚类算法的图像匹配性能较差。此外,随着待匹配图像数量的增加,上述两类算法的计算量急剧上升。针对上述问题,提出一种新的图像匹配判决算法——利用特征点序列截断的匹配判决。该算法利用了匹配特征点之间的匹配度量大于非匹配特征点之间的匹配度量,以及同一匹配簇中来源于同一图像的特征点不超过一个的先验知识,一方面对特征点缺失具有较强的鲁棒性,另一方面克服了上述两类算法中的组合爆炸问题。仿真实验证实了所提算法的有效性。     

Collaborative assignment using belief-desire-intention agent modeling and negotiation with speedup strategies

In this paper, we propose a distributed agent model that applies belief-desire-intention (BDI) reasoning and negotiation for addressing the linear assignment problem (LAP) collaboratively. In resource allocation, LAP is viewed as seeking a concurrent allocation of one different resource for every task to optimize a linear sum objective function. The proposed model provides a basic agent-based foundation needed for efficient resource allocation in a distributed environment. A distributed agent algorithm that has been developed based on the BDI negotiation model is examined both analytically and experimentally. To improve performance in terms of average negotiation speed and solution quality, two initialization heuristics and two different reasoning control strategies are applied, with the latter yielding different variants of the basic algorithm. Extensive simulations suggest that all the heuristic-algorithm combinations can produce a near optimal solution soon enough in some specific sense. The significance and applicability of the research work are also discussed.     

Dynamic analysis of Java program concepts for visualization and profiling

Concept assignment identifies units of source code that are functionally related, even if this is not apparent from a syntactic point of view. Until now, the results of concept assignment have only been used for static analysis, mostly of program source code. This paper investigates the possibility of using concept information within a framework for dynamic analysis of programs. The paper presents two case studies involving a small Java program used in a previous research exercise, and a large Java virtual machine (the popular Jikes RVM system). These studies investigate two applications of dynamic concept information: visualization and profiling. The paper demonstrates two different styles of concept visualization, which show the proportion of overall time spent in each concept and the sequence of concept execution, respectively. The profiling study concerns the interaction between runtime compilation and garbage collection in Jikes RVM. For some benchmark cases, we are able to obtain a significant reduction in garbage collection time. We discuss how this phenomenon might be harnessed to optimize the scheduling of garbage collection in Jikes RVM.