一种无人地面车的轨迹跟踪控制方法

针对无人地面车辆经典轨迹跟踪控制方法的不足,提出了一种基于无人地面车辆运动学模型的轨迹跟踪控制算法。在算法中引入了位姿的纵坐标误差,以加快跟踪的逼近速度,并利用人工驾驶的思想,采用了一种位一姿交替控制的方法,使路径跟踪既准确又快速。仿真结果表明：该方法是有效的,且可使无人地面车具有更好的跟踪性能。     

多机头螺杆机组的优化运行控制

风冷式冷水机组的能效较低,为了提高机组性能,机组被设计成具有2个或多个制冷剂回路的多机头形式。对多机头风冷式冷水机组的运行控制进行了研究,探讨了其优化运行控制策略,利用TRNSYS软件建立了机组模型并进行了验证,最后利用典型的办公建筑来评估采用优化运行控制策略后机组的节能潜力。同常规控制策略相比,单纯优化运行制冷剂回路的控制策略能使机组年度能耗下降6.5%,同时优化运行制冷剂回路和压缩机的控制策略能使机组年度能耗下降7.9%,节能效果显著。     

增程修正弹单炮多发同时弹着火控技术研究

针对大口径火炮使用增程修正弹打远修近问题,建立了增程修正弹单炮多发同时弹着的控制算法,仿真验证了算法可在不同射程上实现单炮多发同时弹着,对发挥舰炮作战效能具有一定的意义。     

助推-滑翔飞行器弹道分段优化研究

通过数值计算得到了升力体飞行器的气动参数,利用Radau伪谱法将助推-滑翔飞行器弹道优化问题转化为非线性规划问题,分别对主动段和滑翔段进行优化,通过仿真得到了飞行器从助推到滑翔的完整弹道,分析了主动段性能指标对飞行器最大射程的影响。研究结果表明,采用主动段关机点速度最大为性能指标的优化方案,其射程最大,且实现难度适中。     

Optimal joint preventive maintenance and production policies

We study joint preventive maintenance (PM) and production policies for an unreliable production‐inventory system in which maintenance/repair times are non‐negligible and stochastic. A joint policy decides (a) whether or not to perform PM and (b) if PM is not performed, then how much to produce. We consider a discrete‐time system, formulating the problem as a Markov decision process (MDP) model. The focus of the work is on the structural properties of optimal joint policies, given the system state comprised of the system's age and the inventory level. Although our analysis indicates that the structure of optimal joint policies is very complex in general, we are able to characterize several properties regarding PM and production, including optimal production/maintenance actions under backlogging and high inventory levels, and conditions under which the PM portion of the joint policy has a control‐limit structure. In further special cases, such as when PM set‐up costs are negligible compared to PM times, we are able to establish some additional structural properties. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.     

挠性航天器变幅值输入成形姿态机动策略

针对变参数挠性航天器的姿态机动问题,在变幅值零振动成形器的基础上,提出了鲁棒性较强的变幅值零振动和零微分成形器设计方法,设计了鲁棒姿态机动策略.该机动策略的控制目标是,将航天器机动到期望状态的同时,消除挠性结构的残余振动.以含转动挠性太阳翼的航天器进行三轴姿态机动为例,进行数值仿真.仿真结果表明,该机动策略对挠性结构频...     

舰艇编队对空防御队形优化配置模型

分析了海上机动编队中防空舰的位置配置对舰艇编队拦截目标效果的影响,通过舰艇对来袭目标拦截概率的推导,建立了被掩护舰的生存概率模型,从而提供了一种解算编队防御队形最佳配置的方法。     

Signal‐to‐interference‐plus‐noise ratio estimation for wireless communication systems: Methods and analysis

The Signal‐to‐Interference‐plus‐Noise Ratio (SINR) is an important metric of wireless communication link quality. SINR estimates have several important applications. These include optimizing the transmit power level for a target quality of service, assisting with handoff decisions and dynamically adapting the data rate for wireless Internet applications. Accurate SINR estimation provides for both a more efficient system and a higher user‐perceived quality of service. In this paper, we develop new SINR estimators and compare their mean squared error (MSE) performance. We show that our new estimators dominate estimators that have previously appeared in the literature with respect to MSE. The sequence of transmitted bits in wireless communication systems consists of both pilot bits (which are known both to the transmitter and receiver) and user bits (which are known only by the transmitter). The SINR estimators we consider alternatively depend exclusively on pilot bits, exclusively on user bits, or simultaneously use both pilot and user bits. In addition, we consider estimators that utilize smoothing and feedback mechanisms. Smoothed estimators are motivated by the fact that the interference component of the SINR changes relatively slowly with time, typically with the addition or departure of a user to the system. Feedback estimators are motivated by the fact that receivers typically decode bits correctly with a very high probability, and therefore user bits can be thought of as quasipilot bits. For each estimator discussed, we derive an exact or approximate formula for its MSE. Satterthwaite approximations, noncentral F distributions (singly and doubly) and distribution theory of quadratic forms are the key statistical tools used in developing the MSE formulas. In the case of approximate MSE formulas, we validate their accuracy using simulation techniques. The approximate MSE formulas, of interest in their own right for comparing the quality of the estimators, are also used for optimally combining estimators. In particular, we derive optimal weights for linearly combining an estimator based on pilot bits with an estimator based on user bits. The optimal weights depend on the MSE of the two estimators being combined, and thus the accurate approximate MSE formulas can conveniently be used. The optimal weights also depend on the unknown SINR, and therefore need to be estimated in order to construct a useable combined estimator. The impact on the MSE of the combined estimator due to estimating the weights is examined. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Bounding the optimal burn‐in time for a system with two types of failure

Burn‐in is a widely used method to improve the quality of products or systems after they have been produced. In this paper, we consider the problem of determining bounds to the optimal burn‐in time and optimal replacement policy maximizing the steady state availability of a repairable system. It is assumed that two types of system failures may occur: One is Type I failure (minor failure), which can be removed by a minimal repair, and the other is Type II failure (catastrophic failure), which can be removed only by a complete repair. Assuming that the underlying lifetime distribution of the system has a bathtub‐shaped failure rate function, upper and lower bounds for the optimal burn‐in time are provided. Furthermore, some other applications of optimal burn‐in are also considered. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。