高温超导电缆直流测试电源平台的搭建

根据高温超导电缆测试用直流电源平台的要求,建立了硬件平台。该平台为模块化结构,具有输出精度高,便于扩展等特点;为方便操作,建立了基于LabVIEW的软件平台,对直流电源平台进行远程控制,并给出了远程控制的程序流程图,实现了电流的匀速上升和下降以及上升过程中的中断操作;利用该电源平台进行了超导电缆的临界电流测试实验,验证了直流电源平台符合高温超导电缆的测试要求。     

变采样周期和多包传输的非线性NCS故障检测

研究具有多包传输、时变采样周期和未知干扰输入的Lipschitz非线性网络控制系统的故障检测问题。利用主动变采样周期的方法将多包传输的非线性连续网络控制系统建模为离散切换系统,设计基于观测器的鲁棒故障检测滤波器构造残差产生系统,运用Lyapunov稳定性理论和线性矩阵不等式(LMI)技术,给出了使闭环系统渐近稳定的充分条件及故障检测滤波器的增益矩阵。最后运用仿真算例说明了故障检测滤波器的残差产生系统对故障具有敏感性,同时对外部扰动输入具有鲁棒性。     

相对主元分析在船舶机舱监控系统的应用

目前船员对于船舶状况、航行状态等的判断主要还是依靠经验,难免会出现不恰当的决策,造成不必要的人力、财力的损失;针对这一问题提出并开发了一套融入相对主元分析船舶机舱监控系统;该系统除了具有常规机舱监控系统功能外,还能实现故障监测功能;协助管理人员进行系统故障的分析,从而更好地保证船舶航行的安全与效率,减少人为误操作带来的事故问题;增强了船舶监控系统的功能,大大提高了人员的工作效率减轻了人员的劳动强度;其设计满足船级社的定期无人机舱值守操作,为机舱监控系统的设计提供了一种新的思路。     

基于C++Builder的换热器性能试验平台测控软件的开发

换热器性能测试是换热器设计过程中的重要环节,对其结构优化及性能评估具有重要作用。针对传统的换热器性能测试系统存在试验周期长、组合方案少,自动化水平不高、可重用应用性较差等不足,文章基于工业控制计算机和C++ Builder软件平台开发了换热器性能试验测控与仿真系统。该系统实现了试验工况参数的控制与过程仿真、试验数据的采集记录与分析处理等各项操作的自动化。文章在简要介绍换热器性能测试系统硬件设计的基础上,具体结合系统硬件介绍了利用C++ Builder制作的换热器仿真实验测控系统的方法及过程,最后给出换热器性能测试仿真实验用户界面及仿真实验运行结果。试验结果表明,测控系统具有交互界面良好、使用方便,可靠性高等特点,能够较好地满足换热器性能测试的要求。     

Optimal Control for Multiscale Elliptic Equations with Rough Coefficients

This paper concerns the convex optimal control problem governed by multiscale elliptic equations with arbitrarily rough $L^\infty$ coefficients, which has not only complex coupling between nonseparable scales and nonlinearity, but also important applications in composite materials and geophysics. We use one of the recently developed numerical homogenization techniques, the so-called Rough Polyharmonic Splines (RPS) and its generalization (GRPS) for the efficient resolution of the elliptic operator on the coarse scale. Those methods have optimal convergence rate which do not rely on the regularity of the coefficients nor the concepts of scale-separation or periodicity. As the iterative solution of the nonlinearly coupled OCP-OPT formulation for the optimal control problem requires solving the corresponding (state and co-state) multiscale elliptic equations many times with different right hand sides, numerical homogenization approach only requires one-time pre-computation on the fine scale and the following iterations can be done with computational cost proportional to coarse degrees of freedom. Numerical experiments are presented to validate the theoretical analysis.     

半线性抛物最优控制问题全离散插值系数有限元方法的收敛性分析

本文考虑全离散插值系数有限元方法求解半线性抛物最优控制问题,其中控制变量用分片常数函数逼近,状态变量和对偶状态变量用分片线性函数逼近.对于方程中的半线性项,先用插值系数技巧处理,再用牛顿迭代法求解.通过引入一些辅助变量和投影算子,并利用有限元空间的逼近性质,得到半线性抛物最优控制问题插值系数有限元方法的收敛性结果;数值算例结果验证了理论结果的正确性.     

Risk-averse stochastic optimal control: An efficiently computable statistical upper bound

In this paper, we discuss an application of the Stochastic Dual Dynamic Programming (SDDP) type algorithm to nested risk-averse formulations of Stochastic Optimal Control (SOC) problems. We propose a construction of a statistical upper bound for the optimal value of risk-averse SOC problems. This outlines an approach to a solution of a long standing problem in that area of research. The bound holds for a large class of convex and monotone conditional risk mappings. Finally, we show the validity of the statistical upper bound to solve a real-life stochastic hydro-thermal planning problem.     

Characterization and computation of control invariant sets for linear impulsive control systems

Impulsive control systems are suitable to describe and control a venue of real-life problems, going from disease treatment to aerospace guidance. The main characteristic of such systems is that they evolve freely in-between impulsive actions, which makes it difficult to guarantee its permanence in a given state-space region. In this work, we develop a method for characterizing and computing approximations to the maximal control invariant sets for linear impulsive control systems, which can be explicitly used to formulate a set-based model predictive controller. We approach this task using a tractable and non-conservative characterization of the admissible state sets, namely the states whose free response remains within given constraints, emerging from a spectrahedron representation of such sets for systems with rational eigenvalues. The so-obtained impulsive control invariant set is then explicitly used as a terminal set of a predictive controller, which guarantees the feasibly asymptotic convergence to a target set containing the invariant set. Necessary conditions under which an arbitrary target set contains an impulsive control invariant set (and moreover, an impulsive control equilibrium set) are also provided, while the controller performance are tested by means of two simulation examples.     

Terminal constrained robust hybrid iterative learning model predictive control for complex time-delayed batch processes

This work mainly addresses terminal constrained robust hybrid iterative learning model predictive control against time delay and uncertainties in a class of complex batch processes with input and output constraints. In this work, an equivalently novel extended two-dimensional switched system is first constructed to represent the process model by introducing state difference, output error and new relaxation variable information. Then, a hybrid predictive updating controller is proposed and an optimal performance index function including terminal constraints is designed. Under the condition that the switching signal meets certain conditions, the solvable problem of model predictive control is realized by Lyapunov stability theory. Meanwhile, the design scheme of controller parameters is also given. In addition, the robust constraint set is adopted to overcome the disadvantage that the traditional asymptotic stability cannot converge to the origin when it involves disturbances, such that the system state converges to the constraint set and meets its expected value. Finally, the effectiveness of the proposed algorithm is verified by controlling the speed and pressure parameters of the injection molding process.     

Event-triggered and self-triggered impulsive control for two-time-scale systems

This paper studies the stability problem of two-time-scale system via event-triggered impulsive control and self-triggered impulsive control. The overall system is modeled with the hybrid formalism. Two Chang transformations are introduced to completely decouple the hybrid system states into flow set and jump set. A composite impulsive controller based on slow and fast system states is proposed, under which the slow and fast subsystems are simultaneously triggered by event-triggered and self-triggered mechanism, respectively. As a result, the stability conditions are derived for the system under event-triggered and self-triggered impulsive control, respectively. Furthermore, the theoretical result of self-triggered impulsive control is applied to the consensus of the interconnected two-time-scale systems. Finally, simulation examples and comparison study show the effectiveness of the proposed control strategies.