MIMO-OFDM系统中的自适应比特分配

正交频分复用(OFDM)与多天线(MIMO)技术的结合可以有效提高系统的性能。为了研究自适应比特分配对MIMO-OFDM系统性能的影响,首先介绍了MIMO-OFDM的系统结构和MIMO信道的奇异值分解(SVD)过程。将多载波系统中的Hughes-Hartogs自适应分配算法应用于天线数为2×2的MIMO-OFDM系统中。仿真结果表明,采用Hughes-Har-togs算法的MIMO-OFDM系统的数据速率达到甚至超过了单天线OFDM(SISO-OFDM)系统的2倍,但SVD分解也带来了巨大的运算量,提出了在MIMO-OFDM系统中使用自适应分配算法的策略。     

一种基于零空间的再分配伪逆算法

由于伪逆法不考虑执行器的位置和速率的限制,因此利用伪逆法设计出的分配器会产生操纵面过早进入饱和的现象,从而使分配器对转矩可达集的分配效率较低.在伪逆法的分配基础上利用控制效率矩阵零空间的特性对分配结果进行二次调节,使伪逆解重新落入执行器的控制子空间,从而避免了分配器过早进入饱和的现象.并提高了分配效率.利用某飞机的数据进行仿真验证,结果显示与伪逆法相比,控制性能有明显改善,提高了分配器的分配效率,且可以对转矩可达集内的转矩实施有效的分配.     

Measuring robustness of computing systems

System builders are becoming increasingly interested in robust design. We believe that a methodology for generating robustness metrics will help the robust design research efforts and, in general, is an important step in the efforts to create robust computing systems. The purpose of the research in this paper is to quantify the robustness of a resource allocation, with the eventual objective of setting a standard that could easily be instantiated for a particular computing system to generate a robustness metric. The paper exposes how not considering the uncertainties can result in gross overestimation of the system capacity, and shows a method for reducing the impact of uncertainty, and even use it to our advantage if the uncertainties are correlated. We present our theoretical foundation for a robustness metric and give its instantiation for a particular system.     

Approximate probabilistic optimization using exact-capacity-approximate-response-distribution (ECARD)

Probabilistic structural design deals with uncertainties in response (e.g. stresses) and capacity (e.g. failure stresses). The calculation of the structural response is typically expensive (e.g., finite element simulations), while the capacity is usually available from tests. Furthermore, the random variables that influence response and capacity are often disjoint. In previous work we have shown that this disjoint property can be used to reduce the cost of obtaining the probability of failure via Monte Carlo simulations. In this paper we propose to use this property for an approximate probabilistic optimization based on exact capacity and approximate response distributions (ECARD). In Approximate Probabilistic Optimization Using ECARD, the change in response distribution is approximated as the structure is re-designed while the capacity distribution is kept exact, thus significantly reducing the number of expensive response simulations. ECARD may be viewed as an extension of SORA (Sequential Optimization and Reliability Assessment), which proceeds with deterministic optimization iterations. In contrast, ECARD has probabilistic optimization iterations, but in each iteration, the response distribution is approximated so as not to require additional response calculations. The use of inexpensive probabilistic optimization allows easy incorporation of system reliability constraints and optimal allocation of risk between failure modes. The method is demonstrated using a beam problem and a ten-bar truss problem. The former allocates risk between two different failure modes, while the latter allocates risk between members. It is shown that ECARD provides most of the improvement from risk re-allocation that can be obtained from full probabilistic optimization.     

解决矩阵链相乘处理器调度问题的一种新算法

本文介绍了矩阵链相乘处理器分配问题和离散处理器分配算法,描述了Lee Heejo等人提出的解决MCSP的处理器分配算法,提出了一种解决MCSP的时间复杂度更低的算法,使处理器能尽量被充分利用,并对三种分配算法进行了比较分析.     

平流层通信平台MAC层的调度方案建模及仿真

平流层升空平台能够满足可提供战时服务、能快速部署,适用于区域性覆盖.为满足平台支持的多用户、多优先权、综合业务的接入策略并解决资源动态分配问题.提出了一种可以满足平台MAC层的服务质量(QoS)和动态带宽分配的调度架构,架构包括移动中心站(MCS)对移动站(MS)的带宽分配和移动站内上行业务的二级带宽调度架构,并根据不同业务需求采用不同的调度算法.仿真结果表明:调度方案能很好的满足所有类型业务的服务质量需求.并提供了较好的公平性,保证了架构的可行性.     

Difficulty and complexity definitions for assembly task allocation and assignment in human–robot collaborations: A review

This paper presents a literature review on the different aspects of task allocation and assignment problems in human–robot collaboration (HRC) tasks in industrial assembly environments. In future advanced industrial environments, robots and humans are expected to share the same workspace and collaborate to efficiently achieve shared goals. Difficulty- and complexity-aware HRC assembly is necessary for human-centric manufacturing, which is a goal of Industry 5.0. Therefore, the objective of this study is to clarify the definitions of difficulty and complexity used to encourage effective collaboration between humans and robots to leverage the adaptability of humans and the autonomy of robots. To achieve this goal, a systematic review of the following relevant databases for computer science was performed: IEEE Xplore, ScienceDirect, SpringerLink, ACM Digital Library, and ASME Digital Collection. The results extracted from 74 peer-reviewed research articles published until July 2022 were summarized and categorized into four taxonomies for 145 difficulty and complexity definitions from the perspectives of (1) definition-use objectives, (2) evaluation objectives, (3) evaluation factors, and (4) evaluation variables. Next, existing definitions were primarily classified according to the following two criteria to identify potential future studies on the formulation of new definitions for human-centric manufacturing: (1) agent specificity and (2) common aspects in manual and robotic assemblies.     

Control allocation technology based on fault diagnosis for the unmanned aerial vehicle system subject to physical constraints and fault reconfiguration mismatch

The problem of the system robustness subject to physical constraints and mismatched fault reconstruction is discussed in this paper. In order to facilitate the design, a four-rotor unmanned aerial vehicle (UAV) system model was selected for research. First, the control allocation model of the nonlinear UAV system with disturbances is shown in the paper. Secondly, a weighted pseudo-inverse method based on adaptive weights is proposed, which reduces the impact of physical constraints on the system. After that, a dynamic weight control allocation method based on the fault efficiency matrix is designed. The weight matrix can dynamically adjust the control distribution law according to the fault estimation value provided by the observer. Then, a dynamic adaptive control allocation method for faults and physical constraints is carried out by combining adaptive weights and dynamic weights. Finally, a simulation example is presented to further illustrate the effectiveness of the algorithm proposed in this paper.     

Harmonic control of a dual-valve hydraulic servo system with dynamically allocated flows

Modern industries face increasing demands to improve the precision and workability of equipment, leading to stringent requirements for hydraulic servo systems in terms of flow, accuracy, and output power. High-flow servo valves and multi-valve synchronous control methods have seen more applications in the industry to meet these demands. However, high-flow servo valves are expensive and have unsatisfactory performance, and synchronous control methods require servo valves to have the same hydraulic characteristics, resulting in higher cost and lower accuracy of high-flow hydraulic servo systems. Also, very little has been conducted on controlling single actuators using multiple valves. In this study, we design a novel dual-valve hydraulic servo system structure with a high-flow proportional directional valve that is connected in parallel with a low-flow servo valve and further develop the mathematical model of this dual-valve system. Next, a harmonic control scheme was proposed, which included a flow allocation layer and trajectory tracking layer. Thereby, we achieved optimal control of two valves, and robust performance was guaranteed. Finally, we investigate the relationships between the flows of two valves, the deadband of the proportional directional valve, and trajectory tracking errors. Experimental results show that the proposed control scheme can effectively adjust the output flow of each valve dynamically according to the tracking trajectory and the hydraulic characteristics of the two valves, and the tracking performance of the servo system is significantly improved. This method is promised to enable the realization of an economical, high-flow, high-precision hydraulic servo system that can be generally used in various fields, such as marine engineering and construction.     

Parallel hyper heuristic algorithm based on reinforcement learning for the corridor allocation problem and parallel row ordering problem

Hyper heuristics is a relatively new optimisation algorithm. Numerous studies have reported that hyper heuristics are well applied in combinatorial optimisation problems. As a classic combinatorial optimisation problem, the row layout problem has not been publicly reported on applying hyper heuristics to its various sub-problems. To fill this gap, this study proposes a parallel hyper-heuristic approach based on reinforcement learning for corridor allocation problems and parallel row ordering problems. For the proposed algorithm, an outer layer parallel computing framework was constructed based on the encoding of the problem. The simulated annealing, tabu search, and variable neighbourhood algorithms were used in the algorithm as low-level heuristic operations, and Q-learning in reinforcement learning was used as a high-level strategy. A state space containing sequences and fitness values was designed. The algorithm performance was then evaluated for benchmark instances of the corridor allocation problem (37 groups) and parallel row ordering problem (80 groups). The results showed that, in most cases, the proposed algorithm provided a better solution than the best-known solutions in the literature. Finally, the meta-heuristic algorithm applied to three low-level heuristic operations is taken as three independent algorithms and compared with the proposed hyper-heuristic algorithm on four groups of parallel row ordering problem instances. The effectiveness of Q-learning in selection is illustrated by analysing the comparison results of the four algorithms and the number of calls of the three low-level heuristic operations in the proposed method.