Approximate dynamic programming via iterated Bellman inequalities

In this paper, we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based on solving linear or semidefinite programs, and produces both a bound on the optimal objective, as well as a suboptimal policy that appears to works very well. These results extend and improve bounds obtained in a previous paper using a single Bellman inequality condition. We describe the methods in a general setting and show how they can be applied in specific cases including the finite state case, constrained linear quadratic control, switched affine control, and multi‐period portfolio investment. Copyright © 2014 John Wiley & Sons, Ltd.     

A modified dynamic surface approach for control of nonlinear systems with unknown input dead zone

This paper focuses on the robust output precise tracking control problem of uncertain nonlinear systems in pure‐feedback form with unknown input dead zone. By designing an extended state observer, the states unmeasurable problem in traditional feedback control is solved, and the lumped uncertainty, which is caused by system unknown functions and input dead zone, is estimated. In order to apply separation principle, finite‐time extended state observer is designed to obtain system states and estimate the lumped uncertainty. Then, by introducing tracking differentiator, a modified dynamic surface control approach is developed to eliminate the ‘explosion of complexity’ problem and guarantee the tracking performance of system output. Because tracking differentiator is a fast precise signal filter, the closed‐loop control performance is significantly improved when it is used in dynamic surface control instead of first‐order filters. The L _∞ stability of the whole closed‐loop system, which guarantees both the transient and steady‐state performance, is shown by the Lyapunov method and initialization technique. Numerical and experiment examples are performed to illustrate our proposed control scheme with satisfactory results. Copyright © 2013 John Wiley & Sons, Ltd.     

Matrix expression and vaccination control for epidemic dynamics over dynamic networks

This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks (SISED-DN) is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.     

仿生波状前缘机翼动态失速控制的数值研究

该文提出了采用波状前缘机翼改善动态失速性能的有效控制方式。通过数值求解雷诺平均N-S方程,对比研究了波状前缘机翼和传统的光滑前缘机翼在动态失速时的力学性能和流动特征,并分析了前缘形状改进和可控拍动参数的影响,探讨有效的控制途径。研究结果表明,在深失速的动态失速控制中,波状前缘翼的复杂涡系能更稳定地附着在上翼面,其力学性能明显优于光滑前缘翼,尤其在大攻角范围内优势明显。波状前缘形状改变对升力能几乎没有影响,但转轴前移、增加拍幅和频率都能提高拍动波状前缘翼的升力。     

Heuristic Dynamic Programming Using Echo State Network For Multivariable Tracking Control Of Wastewater Treatment Process

This paper proposes a heuristic dynamic programming (HDP) scheme to simultaneously control the dissolved oxygen concentration and the nitrate level in wastewater treatment processes (WWTP). Unlike traditional HDP schemes, the optimal control values are calculated in an analytical way by the proposed HDP controller. It can reduce the learning burden of the HDP controller to a great extent. The system model and the evaluation index J are approximated by two echo state networks (ESNs). Gradient‐based learning algorithms are employed to train both ESNs online, and the convergence of the training algorithm is investigated based on Lyapunov theory. The performance of the proposed ESN‐based HDP (E‐HDP) controller is tested and evaluated on a WWTP benchmark. Experimental results demonstrate that the proposed approach can achieve effective performance.     

选煤厂信息物理系统任务调度研究

建立了选煤厂信息物理系统模型,将动态联盟思想引入选煤厂信息物理系统任务调度中,并提出了一种基于改进离散粒子群优化算法的选煤厂信息物理系统任务调度算法。该算法首先采用离散粒子群优化算法进行全局寻优,然后采用禁忌搜索算法进行局部搜索,求得全局最优解。仿真结果表明,该算法提高了任务调度的收敛速度、精度以及处理器的平均利用率。     

基于状态指标的更新决策方法研究

针对设备在实际运行和执行任务时经常涉及到维修、更新报废等管理活动缺乏定量模型支撑的问题,提出了利用典型部件的预测寿命和非典型部件的历史寿命对设备系统级的健康状态进行综合评估的方法,建立了一种以状态指标为决策序列的动态规划更新决策方法;该方法能综合考虑维修费用和更新费用,确定最优更新决策,降低保障费用,有效地提高了设备的经济效益;最后经过案例分析证明了该方法的有效性,对于提高设备的保障能力和经济效益提供了理论支撑和方法指导.     

一种改进的多变量动态矩阵控制算法及应用

为克服重油催化裂化分馏塔控制中存在的满足镇定设计的同时,难以优化系统性能的不足。以PID和DMC(Dynamic Matrix Control)为基础,提出一种新型多变量PIDDMC算法。该算法兼具PID结构简单、参数方便调节,和DMC滚动优化、鲁棒性强的特点。利用Lyapunov稳定性理论证明了该算法可保证系统闭环稳定。以Shell公司重油催化裂化分馏塔为控制对象,仿真验证了该算法克服了PID超调量大,过程输出耦合严重,及DMC绝对误差积分值大的缺点。在模型匹配及模型失配情况下,都具有静态误差小、超调小、调节时间短和鲁棒性强等优点,对多变量过程具有良好的控制效果。     

Nonlinear optimized adaptive trajectory control of helicopter

This paper attempts to develop an optimized adaptive trajectory control system for helicopters based on the dynamic inversion method. This control algorithm is implemented by three time-scale separation architectures. Pseudo control hedging (PCH) is used to protect the adaptive element from actuator saturation nonlinearities and also from the inner-outer-loop interaction. In addition, to augment the attitude control system, two online adaptive architectures that employ a neural network are used. By tuning the neural network based on the system model, a better and faster learning will be achieved, but this is a frustrating and time consuming process. Due to complexity in accurate tuning of neural network, this paper introduces a non-dominated sorting genetic algorithm II (NSGA-II) for off-line optimization of the neural network. Thus, in the proposed method, the neural network can compensate model inversion error caused by the deficiency of full knowledge of helicopter dynamics more accurately. The effectiveness of proposed method is demonstrated by numerical simulations.     

Code Analysis for Software and System Security Using Open Source Tools

ABSTRACT

Software security helps in identifying and managing risks. One of the effective ways to identify software vulnerabilities is to analyze its code. Code analysis (Chess & West, 2007 Chess, B. and West, J. 2007. Secure programming with static analysis, Boston, MA: Addison-Wesley.  [Google Scholar]) helps in catching common coding mistakes such as buffer overflow, unused variables, memory leaks, and various race conditions, which in turn optimizes computer programs, both in storage and computation aspects. Software developers use either open source tools or commercial tools for verification and validation of software. Without proper validation of a software/system using some standard guidelines, potential attackers can find ways to exploit vulnerabilities and bugs and then can gain control over a system, if they are successful. In this paper, we discuss some of the open source static code analysis and dynamic analysis tools, their merits, and limitations with respect to some target codes that contain possible threats. We consider C/C++ and Java programming languages for our experiments. For static code analyzers, we consider Flawfinder, Splint, and Cppcheck; PMD, Findbugs, and Valgrind for dynamic code analysis, and its plug-in, Memcheck, to perform dynamic analysis on executables. We provide our observations in a comparison table, highlighting these tools strengths and weaknesses.