Real-time nonlinear MPC and MHE for a large-scale mechatronic application

Progress in optimization algorithms and in computational hardware made deployment of Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) possible to mechatronic applications. This paper aims to assess the computational performance of NMPC and MHE for rotational start-up of Airborne Wind Energy systems. The capabilities offered by an automatic code generation tool are experimentally verified on a real physical system, using a model comprising 27 states and 4 inputs at a sampling frequency of 25 Hz. The results show the feedback times less than 5 ms for the NMPC with more than 1500 variables.     

Analysis of thermo-mechanical wear problems for reciprocal punch sliding

The relative sliding motion of two elastic bodies in contact induces wear process and contact shape evolution. In the case of a punch sliding on a substrate the transient process tends to a steady state for which the fixed contact stress and strain distribution develops in the contact zone. This state usually corresponds to a minimum of the wear dissipation power. The optimality conditions of the wear dissipation functional provide the contact stress distribution and the wear rate compatible with the rigid body punch motion. The present paper is aimed to extend the previous analyses [1], [2], [3], [4], [5] of steady state conditions to cases of periodic sliding of punch, assuming cyclic steady state conditions for both mechanical and thermal fields.     

Automatic generation algorithm of expected results for testing of component-based software system

ContextA component-based software (CBS) system is a typical example of a composite component, which is composed of two or more atomic components. In the test of a CBS system, it is necessary to automatically generate expected results because they are compared with the actual results.ObjectiveThis paper proposes an automatic generation algorithm of expected results for the testing of a CBS system.MethodThe algorithm analyzes Input/Output (I/O) relationships of a CBS system to identify inputs that influence its outputs. Then, the algorithm uses test cases of atomic components for each input and automatically generates expected results. To evaluate the proposed approach, we compare the proposed approach with the other I/O relationship based approach via two case studies which are the CBS systems for guide robot. The comparison shows the effectiveness of our approach.ResultsTo verify effectiveness of the proposed approach, we measure the cost of manual generation of expected results for each case study. The costs are from 0.001 to 0.015 in the first case study, and are from 0.590 to 0.998 in the second case study.ConclusionThis proposed approach reduces the time-consuming and error-prone task which manually generates expected results for the testing of a CBS system.     

互联电网自动发电控制功率分配的改进逼近于理想解的排序--Q多目标优化算法

本文提出了一种多目标决策与强化学习相结合的改进的逼近于理想解的排序(technique for order preference similar to an ideal solution,TOPSIS)-Q算法,有效解决了自动发电控制(automatic generation control,AGC)总功率指令分配到风电、水电、火电等各类AGC机组的动态随机多目标优化问题.算法采用3个不同的目标Q值矩阵进行迭代更新,然后利用改进TOPSIS方法对Q值矩阵进行多目标决策处理,客观地给出各目标的动态最优权重系数,从而得到各状态-动作对的综合评价判据.IEEE标准两区域模型仿真研究验证了改进TOPSIS-Q算法在AGC机组功率多目标动态优化分配过程应用的可行性和有效性,在复杂随机扰动的环境中提高系统CPS性能的同时,有效降低了AGC机组调节成本和碳排放.     

非确定型离散事件系统双模拟控制的实现

近年来,双模拟等价关系与离散事件系统监控理论相结合的研究引起了国内外许多学者的广泛关注.本文针对作者在前期工作中提出的非确定型离散事件系统的双模拟控制机制,进一步探讨其实现问题.利用投影映射对系统规范说明语言进行等价类划分,构造了一棵计算树,得到了一个判断规范说明是否具有基于模拟关系可观性的多项式算法,证明了双模拟控制机制是多项式时间算法可实现的.同时,通过对控制器配备具有存储和判断功能的模拟关系识别器,阐述了这种双模拟控制机制是物理可实现的.     

具有多传输通道系统的网络化预测控制

本文研究了一类具有多传输通道网络化系统的控制问题,基于网络化预测控制方法,提出了一种改进型的分布式预测补偿方式,从而更有效地利用反馈数据来提高控制系统的性能.对闭环网络化预测控制系统进行分析,得到其稳定性条件,特别地,在模型精确已知和多传输通道的时延为定常的情况下,该条件将会退化为本地控制的闭环系统稳定性条件.上述结论的好处是网络化预测控制系统中状态观测器和控制器的设计可以参考本地控制.通过球杆系统算例验证本文所提方法的正确性和有效性.     

受未知通信时滞影响的高阶多智能体系统的趋同

本文考虑了极点在闭左半平面的高阶连续多智能体系统的趋同问题.假设网络拓扑为有向图,且个体从邻居收到的信息存在通信时滞,分别得到与时滞无关和与时滞有关的两种趋同条件,这两个条件充分揭示了智能体结构、通信时滞和网络拓扑三者之间的关系.本文的核心方法是利用参数化代数Riccati方程的唯一正定解来设计趋同增益.此外,文中说明了通信时滞在有些情况下可为时变的.最后,数值例子验证了所得理论结果的有效性.     

输入有约束时的飞翼布局无人机姿态控制

针对大展弦比飞翼布局无人机的刚体运动与弹性运动耦合动力学模型,研究了输入有约束时的无人机姿态控制问题,提出了一种采用扩张状态观测器的反步滑模控制方法.首先,采用扩张状态观测器实时估计气动弹性模态和外界未知干扰的影响,并引入跟踪微分器避免了控制律中项数膨胀问题.然后,针对飞翼布局无人机多操纵面的配置和输入约束,给出了基于LMI的在线舵面分配算法.最后,针对指令滤波和输入约束情况下控制指令的滞后问题,设计了辅助补偿器对控制指令进行补偿.根据Lyapunov稳定性理论证明了该控制方法能够保证姿态跟踪误差收敛至有界,仿真表明存在复合干扰和输入约束时该方法具有良好的姿态跟踪性能.     

Improving the Performance and Energy E?ciency of Phase Change Memory Systems

Phase change memory (PCM) is a promising technology for future memory thanks to its better scalability and lower leakage power than DRAM (dynamic random-access memory). However, adopting PCM as main me...     

区间时滞相关离散非线性系统的鲁棒模型预测控制

针对一类带有扰动、输入约束和凸多面体不确定性的区间时滞离散非线性系统, 提出一种鲁棒模型预测控制方法. 一方面, 利用min-max 模型预测控制求解鲁棒模型预测控制器, 以研究鲁棒预测控制在范数有界意义下的扰动抑制问题; 另一方面, 充分利用时滞的上下界信息构造Lyapunov 函数以得到控制器存在的充分条件. 最后给出了闭环系统鲁棒稳定性证明.