Improvement of causal analysis using multivariate statistical process control

Statistical process control (SPC) is a conventional means of monitoring software processes and detecting related problems, where the causes of detected problems can be identified using causal analysis. Determining the actual causes of reported problems requires significant effort due to the large number of possible causes. This study presents an approach to detect problems and identify the causes of problems using multivariate SPC. This proposed method can be applied to monitor multiple measures of software process simultaneously. The measures which are detected as the major impacts to the out-of-control signals can be used to identify the causes where the partial least squares (PLS) and statistical hypothesis testing are utilized to validate the identified causes of problems in this study. The main advantage of the proposed approach is that the correlated indices can be monitored simultaneously to facilitate the causal analysis of a software process.

Intelligent adaptive control for MIMO uncertain nonlinear systems

This paper investigates an intelligent adaptive control system for multiple-input–multiple-output (MIMO) uncertain nonlinear systems. This control system is comprised of a recurrent-cerebellar-model-articulation-controller (RCMAC) and an auxiliary compensation controller. RCMAC is utilized to approximate a perfect controller, and the parameters of RCMAC are on-line tuned by the derived adaptive laws based on a Lyapunov function. The auxiliary compensation controller is designed to suppress the influence of residual approximation error between the perfect controller and RCMAC. Finally, two MIMO uncertain nonlinear systems, a mass–spring–damper mechanical system and a Chua’s chaotic circuit, are performed to verify the effectiveness of the proposed control scheme. The simulation results confirm that the proposed intelligent adaptive control system can achieve favorable tracking performance with desired robustness.     

Design of variable structure control for fuzzy nonlinear systems

In this paper, the variable structure control problem is presented for Takagi–Sugeno fuzzy systems with uncertainties and external disturbances. The sliding surfaces for the T–S fuzzy system are proposed by using a Lyapunov function and a fuzzy Lyapunov function, respectively. And we design the variable structure controllers such that the global T–S fuzzy system confined on the sliding surfaces is asymptotically stable. Two examples are given to illustrate the effectiveness of our proposed methods.     

A neural net-based time-delay compensation scheme and disturbance rejection for pneumatic systems

In practical electro-pneumatic or hydraulic servo mechanism, there is usually an unavoidable operating delay time in the solenoid valves. This may sometimes cause closed-loop instability if the time delay is not treated carefully in the control system designs. Furthermore, pneumatic actuators can offer high performance at low cost, but are often suffered from external disturbances depending on the operating conditions. This paper proposes a non-model-based design approach for pneumatic actuating systems. In the proposed control system, a gain scheduled fuzzy-PID controller ensures tracking performance an adaptable wavelet neuro compensator compensates for time-delay of the control valve, and a disturbance rejecter diminishes influence from load changes. A condition ensuring the closed-loop stability is derived. The proposed design is experimentally verified to show its effectiveness.     

Implementation of call admission control scheme in next generation mobile communication networks using particle swarm optimization and fuzzy logic systems

In the present and next generation wireless networks, cellular system remains the major method of telecommunication infrastructure. Since the characteristic of the resource constraint, call admission control is required to address the limited resource problem in wireless network. The call dropping probability and call blocking probability are the major performance metrics for quality of service (QoS) in wireless network. Many call admission control mechanisms have been proposed in the literature to decrease connection dropping probability for handoffs and new call blocking probability in cellular communications. In this paper, we proposed an adaptive call admission control and bandwidth reservation scheme using fuzzy logic control concept to reduce the forced termination probability of multimedia handoffs. Meanwhile, we adopt particle swarm optimization (PSO) technique to adjust the parameters of the membership functions in the proposed fuzzy logic systems. The simulation results show that the proposed scheme can achieve satisfactory performance when performance metrics are measured in terms of the forced termination probability for the handoffs, the call blocking probability for the new connections and bandwidth utilization.     

基于可连Cell的无线传感器网络拓扑控制算法

在无线传感器网络的拓扑控制(TC)中,基于Cell的TC算法被认为是一类可以节省传感器节点能量并延长网络生命周期的方法,但是其需要较多的骨干网节点并且无法保证连通性.通过分析现今算法的内在局限性,提出了一种1-Con思想:当一个Cell的头节点被加入当前骨干网时,所有其可以连接的Cell使用该节点连入拓扑结构,然后此新骨干网递归地继续扩大.基于此思想,设计了一种基于可连Cell的拓扑控制算(CCTC),并从理论上证明:1)CCTC可以保证其所形成的拓扑结构维持网络连通;2)每一轮用于形成骨干网的工作节点非常少.CCTC的计算复杂度是线性的,空间复杂度和信息交换量都是常数量级.仿真实验同样显示,CCTC可以在提供良好鲁棒性和较少的消息交换的情况下,更有效地节省节点能耗并延长网络生命周期.     

Sampled-data based average consensus with measurement noises: convergence analysis and uncertainty principle

In this paper, sampled-data based average-consensus control is considered for networks consisting of continuous-time first-order integrator agents in a noisy distributed communication environment. The impact of the sampling size and the number of network nodes on the system performances is analyzed. The control input of each agent can only use information measured at the sampling instants from its neighborhood rather than the complete continuous process, and the measurements of its neighbors’ states are corrupted by random noises. By probability limit theory and the property of graph Laplacian matrix, it is shown that for a connected network, the static mean square error between the individual state and the average of the initial states of all agents can be made arbitrarily small, provided the sampling size is sufficiently small. Furthermore, by properly choosing the consensus gains, almost sure consensus can be achieved. It is worth pointing out that an uncertainty principle of Gaussian networks is obtained, which implies that in the case of white Gaussian noises, no matter what the sampling size is, the product of the steady-state and transient performance indices is always equal to or larger than a constant depending on the noise intensity, network topology and the number of network nodes.     

The generalization of a class of impulse stochastic control models of a geometric Brownian motion

Recently, international academic circles advanced a class of new stochastic control models of a geometric Brownian motion which is an important kind of impulse control models whose cost structure is different from the others before, and it has a broad applying background and important theoretical significance in financial control and management of investment. This paper generalizes substantially the above stochastic control models under quite extensive conditions and describes the models more exactly under more normal theoretical system of stochastic process. By establishing a set of proper variational equations and proving the existence of its solution, and applying the means of stochastic analysis, this paper proves that the generalized stochastic control models have optimal controls. Meanwhile, we also analyze the structure of optimal controls carefully. Besides, we study the solution function of variational equations in a relatively deep-going way, which constitutes the value function of control models to some extent. Because the analysis methods of this paper are greatly different from those of original reference, this paper possesses considerable originality to some extent. In addition, this paper gives the strict proof to the part of original reference which is not fairly well-knit in analyses, and makes analyses and discussions of the model have the exactitude of mathematical sense. Supported by the National Natural Science Foundation of China (Grant No. 19671004)     

虚拟教室中的共享电子白板的设计和实现

电子白板是虚拟教室中的一个重要工具。该文介绍了基于JAVA语言设计的一个电子白板系统,并对电子白板的设计与实现过程当中的各种关键技术进行了讨论。     

Stability and control of nonlinear systems described by retarded functional equations: a review of recent results

This paper reports on recent results in a series of the work of the authors on the stability and nonlinear control for general dynamical systems described by retarded functional differential and difference equations. Both internal and external stability properties are studied. The corresponding Lyapunov and Razuminkhin characterizations for input-to-state and input-to-output stabilities are proposed. Necessary and sufficient Lyapunov-like conditions are derived for robust nonlinear stabilization. In particular, an explicit controller design procedure is developed for a new class of nonlinear time-delay systems. Lastly, sufficient assumptions, including a small-gain condition, are presented for guaranteeing the input-to-output stability of coupled systems comprised of retarded functional differential and difference equations.