用Delphi开发奖金发放系统

本文介绍了用Delphi7.0开发基于SQL Server数据库的奖金发放系统的构思、设计与实现过程,分析了课题的产生背景、需求目标、开发环境选择、逻辑设计与物理设计等问题。     

一种新型并联机床的驱动输入选择

基于螺旋理论,将并联机床全部分支中可作为驱动输入的运动副锁定后,可以得到作用在动平台上的 约束螺旋．选出与机构的自由度数目相同的约束螺旋与机构本身固有的结构约束螺旋组成约束矩阵,根据约束矩阵 的秩确定输入的合理性．将约束力／力矩矩阵的最小奇异值与最大奇异值之比定义为约束力／力矩各向同性度,并 以此为指标对各驱动输入组合的优劣性进行评价．驱动输入选择结果表明,该并联机床存在5 种合理输入,其中以 UPS 分支中的5 个P 副为驱动输入是最优组合．     

基于扩充的GIX/M/1/N排队系统的主动队列管理算法性能评价模型

为了评价主动队列管理(AQM Active Queue Management)算法的性能,通过在标准的排队系统GIX/M/1/N中嵌入主动队列管理(AQM)算法的方法,建立了一个扩充的GIX/M/1/N排队系统。利用该扩充的GIX/M/1/N排队系统和Internet业务流量自相似性的特征,提出了一种评价AQM算法在非响应业务流量下的性能的分析方法,并据此评价了TD,RED,GRED和Adaptive RED等4个经典的AQM算法。为了验证该分析方法的合理性,利用NS2进行了一系列的仿真实验。结果表明,该分析方法所得结果与仿真实验所得结果一致,因此该分析方法能用于评价AQM算法的性能。     

Reliability-based design optimization of problems with correlated input variables using a Gaussian Copula

The reliability-based design optimization (RBDO) using performance measure approach for problems with correlated input variables requires a transformation from the correlated input random variables into independent standard normal variables. For the transformation with correlated input variables, the two most representative transformations, the Rosenblatt and Nataf transformations, are investigated. The Rosenblatt transformation requires a joint cumulative distribution function (CDF). Thus, the Rosenblatt transformation can be used only if the joint CDF is given or input variables are independent. In the Nataf transformation, the joint CDF is approximated using the Gaussian copula, marginal CDFs, and covariance of the input correlated variables. Using the generated CDF, the correlated input variables are transformed into correlated normal variables and then the correlated normal variables are transformed into independent standard normal variables through a linear transformation. Thus, the Nataf transformation can accurately estimates joint normal and some lognormal CDFs of the input variable that cover broad engineering applications. This paper develops a PMA-based RBDO method for problems with correlated random input variables using the Gaussian copula. Several numerical examples show that the correlated random input variables significantly affect RBDO results.     

Partial state observers for linear systems with unknown inputs

We consider the problem of constructing partial state observers for discrete-time linear systems with unknown inputs. Specifically, for any given system, we develop a design procedure that characterizes the set of all linear functionals of the system state that can be reconstructed through a linear observer with a given delay. By treating the delay as a design parameter, we allow greater flexibility in estimating state functionals, and are able to obtain a procedure that directly produces the corresponding observer parameters. Our technique is also applicable to continuous-time systems by replacing delayed outputs with differentiated outputs.     

MPC for tracking piecewise constant references for constrained linear systems

In this paper, a novel model predictive control (MPC) for constrained (non-square) linear systems to track piecewise constant references is presented. This controller ensures constraint satisfaction and asymptotic evolution of the system to any target which is an admissible steady-state. Therefore, any sequence of piecewise admissible setpoints can be tracked without error. If the target steady state is not admissible, the controller steers the system to the closest admissible steady state.These objectives are achieved by: (i) adding an artificial steady state and input as decision variables, (ii) using a modified cost function to penalize the distance from the artificial to the target steady state (iii) considering an extended terminal constraint based on the notion of invariant set for tracking. The control law is derived from the solution of a single quadratic programming problem which is feasible for any target. Furthermore, the proposed controller provides a larger domain of attraction (for a given control horizon) than the standard MPC and can be explicitly computed by means of multiparametric programming tools. On the other hand, the extra degrees of freedom added to the MPC may cause a loss of optimality that can be arbitrarily reduced by an appropriate weighting of the offset cost term.     

一个手机整句输入算法的研究与实现

随着时代的发展,手机在人们生活中起着越来越重要的作用。目前,相对于其他丰富多采的手机应用,手机输入法研究相对较少。该文针对手机存储空间小、计算能力低的特点,提出了一种整句查找算法。文章首先介绍了使用倒序排列的文件结构,然后根据该文件结构设计出一种宽度为N的整句查找算法,并在手机S60平台上实现了整句输入系统。文章最后对该整句算法的输入正确率进行了测试。实验结果表明,该算法有着较好的效果。     

Event-triggered-based integral reinforcement learning output feedback optimal control for partially unknown constrained-input nonlinear systems

In this paper, an adaptive output feedback event-triggered optimal control algorithm is proposed for partially unknown constrained-input continuous-time nonlinear systems. First, a neural network observer is constructed to estimate unmeasurable state. Next, an event-triggered condition is established, and only when the event-triggered condition is violated will the event be triggered and the state be sampled. Then, an event-triggered-based synchronous integral reinforcement learning (ET-SIRL) control algorithm with critic-actor neural networks (NNs) architecture is proposed to solve the event-triggered Hamilton–Jacobi–Bellman equation under the established event-triggered condition. The critic and actor NNs are used to approximate cost function and optimal event-triggered optimal control law, respectively. Meanwhile, the event-triggered-based closed-loop system state and all the neural network weight estimation errors are uniformly ultimately bounded proved by Lyapunov stability theory, and there is no Zeno behavior. Finally, two numerical examples are presented to show the effectiveness of the proposed ET-SIRL control algorithm.     

Adaptive fault-tolerant control for a class of flexible air-breathing hypersonic vehicles

In this paper, a novel adaptive fault-tolerant control (FTC) scheme is proposed for a class of flexible air-breathing hypersonic vehicles with unknown inertial and aerodynamic parameters and even input constraints. The fault model under consideration covers the case that all actuators suffer from unknown time-varying faults. In the controller design and stability analysis, we introduce new Lyapunov functions, some differentiable auxiliary functions, a bound estimation approach, and a Nussbaum function, which help us successfully circumvent the obstacle caused by the faults, input constraints, and flexible modes. In addition to higher reliability, the proposed scheme is able to ensure that all closed-loop signals are globally uniformly bounded and to steer the tracking errors of altitude and velocity into predefined arbitrarily small residual sets. As a result, the tracking accuracy can be designated in advance. Simulation results illustrate the effectiveness of the proposed scheme.     

Preview control of polytopic time-varying systems subject to actuator saturation

In this study, a novel method is proposed to track a previewable reference signal in the polytopic time-varying system with input saturation. Firstly, an augmented model containing future information is constructed using a new formal variable. This leads to the tracking control problem of polytopic time-varying system with input saturation is transformed into a stability problem of augmented error system. Next, the state and static output feedback preview controls are introduced, and the corresponding controller gains are produced by the proposed conditions. Two examples are presented to validate the effectiveness of the proposed preview controller.