Optimal tracking performance of MIMO discrete‐time systems with communication constraints

The optimal tracking problem for multiple‐input multiple‐output linear‐time‐invariant discrete‐time systems with communication constraints in the feedback path is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. The objective is to obtain an optimal tracking performance, attainable by all possible stabilizing compensators. It is shown that the optimal tracking performance consists of two parts, one depends on the nonminimum phase zeros and zero direction of the given plant, as well as the reference input signal direction, and the other depends on the nonminimum phase zeros, unstable poles, and pole direction of the given plant, as well as the bandwidth and additive white Gaussian noise of the communication channel. It is also shown that, if the constraint of the communication channel does not exist, the optimal tracking performance reduces to the existing tracking performance of the control system without communication constraints. A typical example is given to illustrate the theoretical results. Copyright © 2011 John Wiley & Sons, Ltd.     

Handling multiple objectives with biogeography-based optimization

Biogeography-based optimization (BBO) is a new evolutionary optimization method inspired by biogeography. In this paper, BBO is extended to a multi-objective optimization, and a biogeography-based multi-objective optimization (BBMO) is introduced, which uses the cluster attribute of islands to naturally decompose the problem. The proposed algorithm makes use of nondominated sorting approach to improve the convergence ability effciently. It also combines the crowding distance to guarantee the diversity of Pareto optimal solutions. We compare the BBMO with two representative state-of-the-art evolutionary multi-objective optimization methods, non-dominated sorting genetic algorithm-II (NSGA-II) and archive-based micro genetic algorithm (AMGA) in terms of three metrics. Simulation results indicate that in most cases, the proposed BBMO is able to find much better spread of solutions and converge faster to true Pareto optimal fronts than NSGA-II and AMGA do.     

Optimal Performance in Tracking Stochastic Signal Under Disturbance Rejection

The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H₂ criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results.     

Parallel heap: An optimal parallel priority queue

We describe a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines. To our knowledge, it is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure. Employing p processors, the parallel heap allows deletions of (p) highest priority items and insertions of (p) new items, each in O(log n) time, where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n.This work was supported by U.S. Army's PM-TRADE contract N61339-88-g-0002, Florida High Technology and Industry grant 11-28-716, and Georgia State University's internal research support during spring and summer quarters, 1991.     

基于五层十五级遥感数据结构的并行算法研究

针对当前环境与监测预报小卫星宽覆盖和海量数据显示与处理不足的现状,设计五层十五级遥感数据组织结构,并依据此结构设计一种新的并行计算算法,得到并行计算的最大近优估算值,优化环境与监测预报小卫星海量数据的遥感产品生产能力,提高环境监测预报效率。     

线性矩阵方程异类约束最小二乘解的迭代算法

多矩阵变量线性矩阵方程(LME)约束解的计算问题在参数识别、结构设计、振动理论、自动控制理论等领域都有广泛应用。本文借鉴求线性矩阵方程(LME)同类约束最小二乘解的迭代算法,通过构造等价的线性矩阵方程组,建立了求多矩阵变量LME的一种异类约束最小二乘解的迭代算法,并证明了该算法的收敛性。在不考虑舍入误差的情况下,利用该算法不仅可在有限步计算后得到LME的一组异类约束最小二乘解,而且选取特殊初始矩阵时,可求得LME的极小范数异类约束最小二乘解。另外,还可求得指定矩阵在该LME的异类约束最小二乘解集合中的最佳逼近解。算例表明,该算法是有效的。     

计及多能需求的综合能源服务商优化运行策略研究

随着分布式发电技术的不断成熟及发展,未来综合能源服务将是整合不同类型分布式发电并满足用户不同用能需求的有效途径。提出了一种含有多种分布式发电资源同时考虑多用能需求的综合能源服务商优化运行策略模型。首先建立了含有风电、光伏、燃气轮机、电储能、电热泵、辅助锅炉等分布式资源及电、热用能需求的园区综合能源系统优化调度模型;其次计算优化运行后的能源利用效率;最后,分析对比了不同季节、实时电价及天然气价格变化对综合能源服务商运行策略及盈利的影响。仿真结果验证了模型的有效性,其中综合能源服务商的收益对天然气的价格变化更为敏感。     

陈垃圾滚筒筛运动模式与筛分效率优化

推导陈垃圾在滚筒筛中的运动方程并求数值解,按最大位置角将陈垃圾运动模式划分成滚落、抛落、圆周运动,给出不同筛筒转速、半径、动摩擦因数下的运动模式判别云图. 滚筒筛试验结果显示,陈垃圾运动的最大位置角随转速的升高先增大后不变,转速超过50 r/min后垃圾进行圆周运动. 陈垃圾滚筒筛的筛分效率随转速增大呈先升后降的趋势,随抛落差的增大呈持续上升的趋势,随着原料水的质量分数的增加呈下降的趋势. 基于试验结果,给出滚筒筛最优转速取值云图,在实际工程中可根据垃圾动摩擦因数及滚筒半径选择最优转速,同时减小水的质量分数以提高筛分效率.     

自适应Fourier分解思想在再生核W2 1 [a,b]空间的应用

在再生核$W_2^1[a, b]$空间中研究自适应正交贪婪分解算法, 利用能量下降最快的原理自适应性地构造出最佳$n$项逼近函数, 并从理论上证明其收敛性成立。最后, 实验验证了在$W_2^1[a, b]$再生核空间中, 利用正交贪婪原理构造的$n$项数值原函数比用等分结点构造出的最佳$n$项数值原函数收敛效果更优。