Adaptive receding horizon control for constrained MIMO systems

An adaptive control algorithm for open-loop stable, constrained, linear, multiple input multiple output systems is presented. The proposed approach can deal with both input and output constraints, as well as measurement noise and output disturbances. The adaptive controller consists of an iterative set membership identification algorithm, that provides a set of candidate plant models at each time step, and a model predictive controller, that enforces input and output constraints for all the plants inside the model set. The algorithm relies only on the solution of standard convex optimization problems that are guaranteed to be recursively feasible. The experimental results obtained by applying the proposed controller to a quad-tank testbed are presented.     

Security concepts for the dynamics of autonomous vehicle networks

The secure operation of autonomous vehicle networks in the presence of adversarial observation is examined, in the context of a canonical double-integrator-network (DIN) model. Specifically, we study the ability of a sentient adversary to estimate the full network’s state, from noisy local measurements of vehicle motions. Algebraic, spectral, and graphical characterizations are provided, which indicate the critical role of the inter-vehicle communication topology and control scheme in achieving security.     

基于BACnet/IP的设备与实时数据库通信实现

针对不同厂商、不同系统的楼宇自控设备互操作、互通信的局限性,分析了BACnet/IP技术和实时数据库,设计开发了一种基于BACnet/IP技术的实时数据库DasRdb的设备驱动程序。该设备驱动程序采用UDP通信方式,通过调用每个BACnet/IP设备的标准接口函数来驱动实时数据库DasRdb分别进行写操作和读操作,能够有效地实现BACnet/IP设备与实时数据库DasRdb之间的通信,从而使楼控设备的互操作成为可能。现场工程应用表明,该程序的运行契合BACnet的一致性要求,具有简单、高效、精确度高、实时性好的特点。     

案例式教学法在《Access数据库》教学中的应用研究

作为一门重要的数据库基础课程,《Access数据库》的教学不但可以使学生学会一种数据库技术,而且还能够奠定学生将来学习高级数据库技术的基础,因此,将案例式教学法应用《Access数据库》教学中具有重大的实际意义。为此,对案例式教学法的内涵进行阐述,《Access数据库》教学中案例式教学法的实际应用策略,以及应用案例式教学法需要注意的一系列事项。     

基于 Android 系统的飞行射击游戏框架设计与实现

在飞行射击游戏框架设计与实现过程中,分析游戏的场景设计、物体之间碰撞的处理、游戏角色和整个游戏类的框架并对程序流程进行描述。实现游戏UI的设计、背景的载人、角色的设计和实例化。在Android系统中对该游戏进行反复测试,实现飞行射击游戏。     

一种实验用双色染料搅拌机的结构设计与控制实现

根据教学实验需要,创新设计了一种双色染料搅拌机的主体结构,为保证设备的有效使用,将其中的主要支承部件利用Solidworks进行了三维造型设计,并运用SimulationXpress分析向导对其应力状态、安全系数进行仿真优化,最后通过Siemens S7-200 PLC对其整体结构进行控制,能够完全的满足需要.本装置有控制过程简单方便、结构新颖、占用空间小等优点,具有良好的推广与应用价值.     

YL-1OO型自动加药装置在乙烯循环水场的应用

介绍了国产YL-100型自动加药装置功能及其在中国石化茂名石化乙烯工业公司乙烯循环水场的应用情况,结果表明其运行平稳,总磷测试数据可靠,可达到循环水自动加药控制的目的。     

On the complexity of role updating feasibility problem in RBAC

In Role Based Access Control (RBAC) systems, it is necessary and important to update the role–permission assignments in order to reflect the evolutions of the system transactions. However, role updating is generally complex and challenging, especially for large-scale RBAC systems. This is because the resulting state is usually expected to meet various requirements and constraints. In this paper, we focus on a fundamental problem of role updating in RBAC, which determines whether there exists a valid role–permission assignment, i.e., whether it can satisfy all the requirements of the role updating and without violating any role–capacity or permission–capacity constraint. We formally define such a problem as the Role Updating Feasibility Problem (RUFP), and study the computational complexity of RUFP in different subcases. Our results show that although several subcases are solvable in linear time, this problem is NP-complete in the general case.     

Association-Based Active Access Control models with balanced scalability and flexibility

In existing Active Access Control (AAC) models, the scalability and flexibility of security policy specification should be well balanced, especially: (1) authorizations to plenty of tasks should be simplified; (2) team workflows should be enabled; (3) fine-grained constraints should be enforced. To address this issue, a family of Association-Based Active Access Control (ABAAC) models is proposed. In the minimal model ABAAC₀, users are assigned to roles while permissions are assigned to task-role associations. In a workflow case, to execute such an association some users assigned to its component role will be allocated. The association's assigned permissions can be performed by them during the task is running in the case. In ABAAC₁, a generalized association is employed to extract common authorizations from multiple associations. In ABAAC₂, a fine-grained separation of duty (SoD) is enforced among associations. In the maximal model ABAAC₃, all these features are integrated, and similar constraints can be specified more concisely. Using a software workflow, case validation is performed. Comparison with a representative association based AAC model and the most scalable AAC model so far indicates that: (1) enough scalability is achieved; (2) without decomposition of a task, different permissions can be authorized to multiple roles in it; (3) separation of more fine-grained duties than roles and tasks can be enforced.     

Data-driven asymptotic stabilization for discrete-time nonlinear systems

In this paper, we propose a data-driven feedback controller design method based on Lyapunov approach, which can guarantee the asymptotic stability of the closed-loop and enlarge the estimate of domain of attraction (DOA) for the closed-loop. First, sufficient conditions for a feedback controller asymptotically stabilizing the discrete-time nonlinear plant are proposed. That is, if a feedback controller belongs to an open set consisting of pairs of control input and state, whose elements can make the difference of a control Lyapunov function (CLF) to be negative-definite, then the controller asymptotically stabilizes the plant. Then, for a given CLF candidate, an algorithm, to estimate the open set only using data, is proposed. With the estimate, it is checked whether the candidate is or is not a CLF. If it is, a feedback controller is designed just using data, which satisfies sufficient conditions mentioned above. Finally, the estimate of DOA for closed-loop is enlarged by finding an appropriate CLF from a CLF candidate set based on data. Because the controller is designed directly from data, complexity in building the model and modeling error are avoided.