车辆高速避让路径跟踪控制策略

建立车辆动力学模型,研究车辆在高速避让工况下的路径跟踪控制策略。基于自抗扰控制设计车辆横摆角速度以及道路曲率2种不同的路径跟踪控制器;设计基于车辆偏航位移和偏航角度加权的线性二次最优控制器;对3种控制器控制效果进行仿真验证,分析路径跟踪侧向位移误差、侧向加速度、前轮转向角以及偏航角度变化。越野车实车测试结果表明,路径跟踪控制策略正确。     

HACCP在浓香菜籽油生产中的应用

为了保障浓香菜籽油的产品质量安全,采用HACCP体系对浓香菜籽油生产全过程进行生物、物理、化学的危害分析,确定关键控制点,制定预防措施,并对生产环节进行有效监控,制定纠偏措施,做好记录管理,为浓香菜籽油的安全生产提供借鉴。     

焦炉前反馈热工控制系统运行实践

焦炉生产是典型的大惯性、非线性、时变快的复杂系统，以“火落温度”为基础的焦炉前反馈热工控制系统，通过立火道温度自动测量与人工测温相关性分析、粗煤气温度测量与火落判断、标准温度的优化等运行实践，达到了自动火落时间判断、标准温度指导、加热和燃烧优化、高低温炉号判别等目的，对于稳定炉温、降低回炉煤气消耗、提高焦炭质量以及推进焦化企业技术进步具有重要意义。     

密文策略属性加密中的撤销控制方案

在云环境下使用数据共享功能时，由于云环境的复杂性，需要对数据进行安全保护和访问控制，这就要求使用加密机制。基于密文策略属性的加密（CP-ABE）是当前广泛使用的加密机制，它可以根据用户的属性来设置访问权限，任何具有合格访问权限的用户都可以访问数据。然而云是一个动态环境，有时可能只允许具有访问权限用户中的一部分用户访问数据，这就需要用户权限的撤销机制。然而，在CP-ABE中，访问权撤销或用户撤销是一个冗长且代价高昂的事件。所提出方案根据对CP-ABE流程的改进，在原密文中嵌入了可灵活控制的用户个人秘密，使得用户权限撤销时既不要求使用新访问策略的用户撤销数据，也不要求对数据进行重新加密，大幅减少撤销时的计算成本。与知名CP-ABE撤销方案对比，所提出方案的计算成本更低且具有良好的安全性。     

面向噪声丢包感知的无线网络拥塞算法

针对无线网络链路干扰大、误码率高等特点，以及TCP Westwood算法（TCPW）存在估算带宽时过度依赖包的反馈，缺乏区分传输过程中丢包类型的缺点等问题，提出一种TCPW拥塞控制优化算法--TCPW-F。该算法利用发送速率等构建拥塞因子[F]作为判断丢包类型的依据，同时对判定发生噪声丢包时的拥塞窗口进一步调整，避免噪声丢包引起的窗口下降，提高该情况下窗口的发送效率。仿真结果表明，TCPW-F算法在时延性能方面表现更优，单位时间抖动趋于稳定的速度更快。在同一信道带宽下增大包生成速率，改进算法的实时吞吐量明显高于原算法，具备一定的噪声丢包感知能力，无线网络的TCP传输质量获得较大改善。     

机器人系统有限时间自适应迭代学习控制

研究任意初态下，机器人系统的有限时间自适应迭代学习控制方法。引入初始修正吸引子的概念，构造一个含有初始修正项的误差变量。针对定常机器人系统和时变机器人系统，采用Lyapunov-like方法，分别设计迭代学习控制器处理系统中不确定性。并且，采用未含/含限幅学习机制，保证闭环系统各变量的一致有界性和误差变量在整个作业区间一致收敛性。藉以实现跟踪误差在预先指定区间的完全跟踪。仿真结果验证所设计控制方法的有效性。     

基于LBT-SA的LoRaWAN信道接入方法研究

标准LoRaWAN协议中定义的纯ALOHA信道接入方法在网络负载较大时会造成大量碰撞，使LoRa网络的可扩展性和可靠性受到极大挑战。为此提出了一种将先听后说与模拟退火相结合（Listen Before Talk combined with Simulated Annealing，LBT-SA）的LoRa信道接入方法。该方法通过在设备发送之前先监听信道，降低信道被同时接入的概率，并以成功传输所需退避时间为初始值，搜索更小的退避时间。仿真结果表明，LBT-SA和基于二元指数退避算法的先听后说（Listen Before Talk，LBT）方法在包成功传输率方面保持了高度的一致，并且LBT-SA在周期传输过程中逐渐减少了不必要的退避时间，从而减少了时延。在多达10 000个终端接入单个网关的场景中，该算法的平均退避时间至少降低了16.38%。     

An iterative approach for the discrete‐time dynamic control of Markov jump linear systems with partial information

The , and mixed dynamic output feedback control of Markov jump linear systems in a partial observation context is studied through an iterative approach. By partial information, we mean that neither the state variable x(k) nor the Markov chain θ(k) are available to the controller. Instead, we assume that the controller relies only on an output y(k) and a measured variable coming from a detector that provides the only information of the Markov chain θ(k). To solve the problem, we resort to an iterative method that starts with a state‐feedback controller and solves at each iteration a linear matrix inequality optimization problem. It is shown that this iterative algorithm yields to a nonincreasing sequence of upper bound costs so that it converges to a minimum value. The effectiveness of the iterative procedure is illustrated by means of two examples in which the conservatism between the upper bounds and actual costs is significantly reduced.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Discrete‐time sector based hands‐off control for nonlinear system

This article presents a hands‐off control design for discrete‐time nonlinear system with a special type of nonlinear sector termed as “discrete‐time sector.” The design method to define the boundary of a discrete‐time sector is done with control‐Lyapunov function. The generalization of nonlinear system is viewed in the perspective of a comparison function. By means of a proposed sector, a switching control is designed such that no control action is experienced inside the sector thus, saving unnecessary control efforts. However, to study the robustness for discrete‐time system, a hands‐off control is modified to ensure the monotonic decrease in the energy of the system. Finally, the proposed approach is verified with the simulation results.