基于滑模自适应控制的不确定混沌系统修正函数投影同步

研究了一类不确定混沌系统的修正函数投影同步。首先,设计了一类滑模曲面;基于该曲面设计了同步控制器,并采用自适应技术设计了自适应律对不确定参数进行逼近。在一定条件下,该同步控制方案可以实现2个不确定异结构混沌系统的修正函数投影同步。然后,为保证合适的控制量,对控制增益进行了优化。从同步效果来看,所设计的控制器对混沌系统的不确定项的影响具有较强的鲁棒性。最后,数值仿真验证了该控制器的有效性和可行性。     

基于主动失谐优化的叶轮瞬态加减速振动抑制

提出了一种基于主动失谐优化的叶轮瞬态加减速振动抑制方法.首先建立了瞬态加减速激励下的叶轮降阶模型,获得了表征失谐对瞬态振幅影响的失谐放大因子.然后基于降阶模型,采用蒙特卡洛仿真快速计算了一系列瞬态激励下失谐放大因子的概率密度分布,结果表明:失谐放大因子在大多数瞬态激励下受到随机小失谐的影响大于在稳态激励下受到的影响,且...     

滑动运行继电式激光制导系统

 继电控制式激光制导系统的简单性使它具有高可靠性、低成本等优点。而系统自振使得弹着点散布大,降低了制导精度。将滑动运动模态引人系统,使其变成滑动运行的继电控制方式。结果,弹着点散布压缩,制导精度提高,而且保持了原系统的优点。介绍了该系统的组成,分析了提高制导精度的原理,并提供一些仿真结果。     

Design and Application of Discrete Sliding Mode Control with RBF Network-based Switching Law

This article proposes a novel approach combining exponential-reaching-law-based equivalent control law with radial basis function (RBF) network-based switching law to strengthen the sliding mode control (SMC) tracking capacity for systems with uncertainties and disturbances. First, SMC discrete equivalent control law is designed on the basis of the nominal model of the system and the adaptive exponential reaching law, and subsequently, stability of the algorithm is analyzed. Second, RBF network is used to form the switching law in a direct and online manner with sliding-mode-related inputs and by approximating evaluation function; and the method to adjust its parameters is devised. Finally, comparable experiments are carried out to verify the application of the proposed approach to an inner-axis driven by a direct current (DC) torque motor through extra-low speed servo for a high precision flight simulator, and the axis works under deteriorating conditions such as periodically fluctuating torques of motor, nonlinear friction, and time-varying model parameters. The results show that the combined SMC can effectively improve the servo performance, for instance, to a stable 0.000 08 (°)/s speed response, the tracking error would be within 0.000 08° in 98% of operating times. Moreover, the hybrid nature of the approach imparts the RBF network the features of removing offline training and ease to set initial parameters.     

空间群Pn3mPn3P23子群链耦合系数的计算

本文利用陈金全教授的本征函数法计算了Pn3m Pn3 P2 3空间群的母分系数。最后的计算结果表明 ,用陈金全教授的本征函数法所求得的母分系数确实满足幺正、归一性 ,同时也证明了本征函数法对于求母分系数同样适用     

关于“用好的作风选人，选作风好的人”的逻辑梳理

“用好的作风选人，选作风好的人”必须确定相关的概念，必须进行科学的判断，必须进行正确的推理。本文试图从逻辑角度对这一选人用人原则进行梳理。     

考虑输入饱和的固定翼无人机自适应增益滑模控制

针对复杂环境下的固定翼无人机飞行控制问题，考虑输入饱和以及复杂外界干扰的影响，提出一种基于自适应滑模控制方法的固定翼无人机飞行控制策略。首先，对固定翼无人机模型进行介绍，将模型分为姿态子系统和速度子系统；其次，针对姿态子系统和速度子系统的特点以及控制需求，分别采用自适应多变量螺旋滑模和自适应快速超螺旋滑模设计姿态控制器和速度控制器，该策略无需设计干扰观测器对外界干扰进行估计，仍然可以实现固定翼无人机对姿态参考指令和速度参考指令的有限时间精确跟踪，并基于Lyapunov的稳定性分析方法证明了闭环系统的稳定性。最后，对本文所提出的控制策略进行了仿真验证，结果表明该控制策略具有良好的控制性能。     

航天器近距离交会的固定时间终端滑模控制

针对航天器近距离交会段的位置姿态耦合控制问题，假设航天器受外界干扰且目标航天器存在空间自由翻滚情形时，基于固定时间概念设计了一种六自由度位姿终端滑模自适应控制器，通过引入显含正弦函数的切换项来避免奇异问题。此外所设计的控制器含双幂次项，不仅能全局提高姿态和位置的跟踪速度及精度，还能估计系统稳定所需的时间上界，且该上界与状态初始值无关。基于Lyapunov方法分析了闭环系统的固定时间稳定性。仿真结果表明，该控制器能快速实现对航天器近距离交会时相对位置和姿态的控制，具有较高的精度和良好的干扰抑制能力。     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

Gaussian mixture model based adaptive control for uncertain nonlinear systems with complex state constraints

This paper addresses an uncertain nonlinear control system problem with complex state constraints and mismatched uncertainties. A novel Gaussian Mixture Model(GMM) based adaptive PID-Nonsingular Terminal Sliding Mode Control(NTSMC)(GMM-adaptive-PID-NTSMC)method is proposed. It is achieved by combining a GMM based adaptive potential function with a novel switching surface of PID-NTSMC. Next, the stability of the closed-loop system is proved.The main contribution of this paper is that the GMM meth...