Backstepping Sliding Mode Trajectory Tracking via Extended State Observer for Quadrotors with Wind Disturbance

To overcome nonlinear, underactuated and external wind disturbances problems for the 6-DOF (degrees of freedom) quadrotor unmanned aerial vehicle (UAV) system, a backstepping sliding mode control algorithm based on high-order extended state observer (ESO) is proposed. Based on the hierarchical control principle, the quadrotor UAV dynamic system is decomposed into position subsystem and attitude subsystem to facilitate the backstepping control design. Moreover, the EXO is used to estimate the remaining unmeasurable states and the external wind disturbances online. The advantages of the controllers are that they can not only ensure good tracking performance, but also deal with uncertain external disturbances. To imitate the real situation as much as possible, the external wind disturbances are composed of four basic wind models in this paper. The tracking error and estimate error of the design methods are shown to arbitrarily small by using Lyapunov theory. Finally, the effectiveness and superiority of the proposed control algorithm are proved by the simulation.

     

Finite-time Containment Control of Nonlinear Delayed Fractional Multi-agent Systems

This article deals with finite-time containment control (FTCC) of nonlinear delayed fractional multi-agent systems (FMASs). Addressing fractional Razumikhin approach, properties of fractional calculus and analytical techniques, a quadratic Lyapunov function is constructed to derive sufficient conditions on FTCC by adopting a discontinuous control protocol, the employed method may overcome well the troubles arising from time delays and fractional derivatives. Numerical simulations further clarify the reliability and validity of our theoretical conclusions.

     

Semi-global Adaptive Bipartite Output Consensus of Multi-agent Systems Subject to Input Saturation and External Disturbance Under Switching Network

This paper investigates semi-global adaptive bipartite output consensus of continuous-time multi-agent systems (MASs) with input saturation and non-identical external disturbance under jointly connected switching network. An adaptive bipartite output consensus protocol of MASs is proposed by using low-gain feedback technology. It is turned out that semi-global adaptive bipartite consensus of MASs can be achieved under the protocol. Furthermore, the proposed control protocol can be applied for MASs under fixed network, and semi-global adaptive bipartite output consensus can be also achieved in this case. Finally, the simulations will verify the effectiveness of theoretical results.

     

Neural network-based adaptive decentralized learning control for interconnected systems with input constraints

In this paper, the neural network-based adaptive decentralized learning control is investigated for nonlinear interconnected systems with input constraints. Because the decentralized control of interconnected systems is related to the optimal control of each isolated subsystem, the decentralized control strategy can be established by a series of optimal control policies. A novel policy iteration algorithm is presented to solve the Hamilton–Jacobi–Bellman equation related to the optimal control problem. This algorithm is implemented under the actor-critic structure where both neural networks are simultaneously updated to approximate the optimal control policy and the optimal cost function, respectively. The additional stabilizing term is introduced and an improved weight updating law is derived, which relaxes the requirement of initial admissible control policy. Besides, the input constraints of interconnected systems are taken into account and the Hamilton–Jacobi–Bellman equation is solved in the presence of input constraints. The interconnected system states and the weight approximation errors of two neural networks are proven to be uniformly ultimately bounded by utilizing Lyapunov theory. Finally, the effectiveness of the proposed decentralized learning control method is verified by simulation results.     

Research on Variable Structure and Adaptive Control for Strap-on Rocket

固体捆绑运载火箭变结构自适应控制

陈曦,刘玉玺,汪轶俊

（上海宇航系统工程研究所）

创新点说明：

对于新型固体捆绑火箭而言,由于箭体安装固体助推器,存在推力偏差较大、推力同步性较大的问题,导致火箭的结构干扰增大。安装尾翼外干扰增大,如经过大风区时,风干扰对箭体产生较大的影响。同时考虑建立动力学模型的过程中存在的参数不确定性、参数摄动、三通道间耦合的问题,传统的控制方法难以满足新型固体捆绑火箭的要求,因此本文率先将基于模型参考的变结构自适应控制方法应用于固体捆绑运载火箭上。

研究目的：

本文针对固体捆绑运载火箭控制系统的特点,应用变结构自适应控制理论,设计适用于固体捆绑运载火箭的控制系统,保障固体捆绑运载火箭的正常飞行。

研究方法：

（1）建立固体捆绑运载火箭动力学模型,考虑模型中参数不确定性、未建模动态及通道间耦合;

（2）分析固体捆绑运载火箭存在的干扰,例如：四个固体助推带来的推力偏差、推力不同步性、推力线偏斜,质心横移、芯级、发动机及尾翼安装误差、芯级发动机液体燃料晃动、箭体弹性振动等各类结构误差及风干扰等外干扰;

（3）针对固体捆绑运载火箭设计变结构自适应控制律的设计并证明其稳定性;

（4）Simulink仿真分析验证。

结果：

本文使用变结构自适应控制理论设计的控制系统可全局渐进稳定,三通道姿态角跟踪误差较小,姿态角收敛速度较快,系统性能良好,可有效处理各类结构干扰、外干扰、气动参数不确定性及未建模动态等问题,该控制系统的动态特性及控制品质良好,具有工程应用的前景。

结论：

本文将基于模型参考的变结构自适应控制方法应用于新型固体捆绑运载火箭的控制系统的设计中。给出了仅有俯仰方向有大姿态变动的条件下的火箭动力学偏量模型,并在此基础上设计变结构自适应控制律,同时证明了该控制系统的稳定性。本文通过理论及仿真分析,证明了变结构自适应控制理论在新型固体捆绑运载火箭上的应用可行性,具有一定的工程应用前景。

关键词：运载火箭;模型参考;变结构控制;自适应控制

     

An automatic parameter calibration method for the SWAT model in runoff simulation

Runoff simulation is highly significant for hydrological monitoring, flood peak simulation, water resource management, and basin protection. Runoff simulation by distributed hydrological models, such as the soil and water assessment tool (SWAT) model which is the most widely used, is becoming a hotspot for hydrological forecasting research. However, parameter calibration is inefficient and inaccurate for the SWAT model. An automatic parameter calibration (APC) method of the SWAT model was developed by hybrid of the genetic algorithm (GA) and particle swarm optimization (PSO). Multi‐station and multi‐period runoff simulation and accuracy analysis were conducted in the basin of the Zhangjiang River on the basis of this hybrid algorithm. For example, in the Yaoxiaba Station, the calibration results produced an R² of 0.87 and Nash Sutcliffe efficiency (NSE) index of 0.85, while verification results revealed an R² of 0.83 and NSE of 0.83. Results of this study show that the proposed method can effectively improve the efficiency and simulation accuracy of the model parameters. It can be concluded that the feasibility and applicability of GA‐PSO as an APC method for the SWAT model were confirmed via case studies. The proposed method can provide theoretical guidance for many hydrological research fields, such as hydrological simulation, flood prevention, and forecasting.     

车联网仿真测试评价技术研究综述

智能化和网联化是汽车发展的重要方向,车联网技术作为智能网联汽车体系架构的重要组成部分,近年来成为业界的研究热点之一。车联网的大规模部署及其在智能汽车领域的广泛应用前需要对其性能及功能进行全面、深入的测试评价,然而在真实环境下进行车联网的测试与评估存在成本高、难度大的问题,因此通过仿真手段对其进行评价分析是当前的主流测试手段。本文总结了主流的网络仿真器和交通仿真器,对现有车联网仿真平台进行了分类,研究并对比分析了典型的车联网仿真平台;针对车联网的应用特性,研究并归纳了影响车联网仿真性能的车辆移动模型、信道传播模型及驾驶员行为等;从网络仿真指标、车联网应用相关指标归纳了车联网功能及性能测试的典型评价指标。     

不完备系统多准则决策的云PDR方法

针对多准则决策问题的意义以及经典粗糙集方法在不完备系统方案排序问题中的不足,在前人基于概率优势关系(PDR)排序方法的基础上,结合云理论提出了基于云概率优势关系的不完备系统多准则决策方法,即云PDR排序法。将期望、熵、超熵等参数引入PDR方法,充分考虑了决策的模糊性、波动性和随机性,评价过程和结果更加客观全面。以煤炭资源型城市为例进行应用研究,获得其中各城市发展水平及其波动情况的排序,并通过与其他方法结果的比较验证了本文方法的优势与有效性。     

基于多重约束的OpenXML复合文档内容源数据区容错定界算法

在高误码率条件下,接收到的OpenXML复合文档往往因数据含错而无法打开,而在文档修复过程中,对信源中每个源文件内容源数据区的定界经常容易出错,针对该问题,提出了一种基于多重约束的OpenXML复合文档内容源数据区容错定界算法。通过对文档协议冗余的分析与归类,将内容源数据区定界问题转化为对起始位置序列的最佳估计问题。在通过适当放宽匹配条件完成粗定界的基础上,利用冗余信息中的约束关系构建代价函数对观测数据进行筛选,有效地剔除“虚警”情况,进而实现对内容源数据区起始位置序列的最佳估计。仿真结果表明,在参数设置合理的情况下,该方法具有较好的容错定界能力。     

Chaos synchronization with dual-channel time-delayed couplings

While the significance of oscillator dynamics and coupling structure to synchronization behaviors has been well addressed in the literature, little attention has been paid to the possible influence of coupling functions. In the present paper, adopting the scheme of dual-channel time-delayed couplings, we investigate how the synchronization behaviors of networked chaotic oscillators are influenced by parameters in the coupling functions. It is found that, with the introduction of the second coupling channel, the synchronization region, as calculated according to the method of master stability function (MSF), can be largely modified. In particular, by a slight change of the time delay, it is found that the synchronization region can be significantly adjusted, or even switched from non-existing to existing. We demonstrate this interesting phenomenon for both situations of processing and propagation induced time delays, as well as for different coupling functions. Our studies shed new light on the mechanism of chaos synchronization, and may potentially be used for the control of complex network dynamics.