Building hybrid access control by configuring RBAC and MAC features

ContextRole-Based Access Control (RBAC) and Mandatory Access Control (MAC) are widely used access control models. They are often used together in domains where both data integrity and information flow are concerned. However, there is little work on techniques for building hybrid access control of RBAC and MAC.ObjectiveIn this work, we present a systematic approach for developing a hybrid access control model using feature modeling with the aim of reducing development complexity and error-proneness.MethodIn the approach, RBAC and MAC are defined in terms of features based on partial inheritance. Features are then configured for specific access control requirements of an application. Configured features are composed homogeneously and heterogeneously to produce a hybrid access model for the application. The resulting hybrid model is then instantiated in the context of the application to produce an initial design model supporting both RBAC and MAC. We evaluate the approach using a hospital system and present its tool support.ResultsRBAC and MAC features that are specifically configured for the application are systematically incorporated into a design model. The heterogeneous features of RBAC and MAC are not only present in the resulting model, but also semantically composed for seamless integration of RBAC and MAC. Discharging the proof obligations of composition rules to the resulting model proves its correctness. The successful development of the prototype demonstrates its practicality.ConclusionFeatures in the access control domain are relatively small in size and are suitable to be defined as design building blocks. The formal definition of partial inheritance and composition methods in the presented approach enables precisely specifying access control features and feature configuration, which paves the way for systematic development of a hybrid access control model in an early development phase.     

A multiple model approach for predictive control of nonlinear hybrid systems

This paper presents modeling and control of nonlinear hybrid systems using multiple linearized models. Each linearized model is a local representation of all locations of the hybrid system. These models are then combined using Bayes theorem to describe the nonlinear hybrid system. The multiple models, which consist of continuous as well as discrete variables, are used for synthesis of a model predictive control (MPC) law. The discrete-time equivalent of the model predicts the hybrid system behavior over the prediction horizon. The MPC formulation takes on a similar form as that used for control of a continuous variable system. Although implementation of the control law requires solution of an online mixed integer nonlinear program, the optimization problem has a fixed structure with certain computational advantages. We demonstrate performance and computational efficiency of the modeling and control scheme using simulations on a benchmark three-spherical tank system and a hydraulic process plant.     

基于降阶位置/力模型的机器人神经网络控制

双足机器人的双脚支撑期是实现其步行运动的重要过程,然而耦合的位置/力控制难以保证其稳定平滑运动.本文提出了一种基于降阶位置/力模型的机器人控制策略,整合了位置控制子空间模型和力控制子空间模型,通过模型降阶减小了控制器设计的复杂度,并采用神经网络自适应控制方法综合多控制目标,实现了双足机器人的平滑稳定控制并有效地抑制了系统外扰和参数不确定性的影响.最后,仿真算法验证了该控制方法和模型的有效性.     

混杂系统的研究进展

混杂系统理论和应用是近年来的一个研究热点．在介绍混杂系统概念的基础上，对混杂系统研究中的常用模型进行分类比较，并对混杂系统的性质分析和混杂控制设计中的主要内容和主要研究方法进行总结，最后对今后的研究方向做了总体展望。     

五杆四驱动平面双足机器人动态步态规划与非线性控制

以五杆四驱动的平面双足步行机器人为对象,研究了其动态步行的时不变步态规划和限定时间的非线性控制策略．揭示了其模型的欠驱动和完全驱动的混杂和非光滑动力学特性,推导了其碰撞模型．基于虚拟约束的概念,提出时不变步态的输出函数解析设计方法,设计了反馈线性化控制器,将系统转化为双积分环节．然后采用限定时间控制器在一步内零化输出函数．仿真实验表明,动态步行趋于一个稳定的极限环,实现了规划的行走模式,验证了该方法的有效性．     

Fault detection model‐based controller for process systems

This paper develops a model‐based control system for fault detection and controller reconfiguration using stochastic model predictive control (MPC). The system can determine online the optimal control actions, detect faults quickly, and reconfigure the controller accordingly. Such a system can perform its function correctly in the presence of internal faults. A fault detection model based (FDMB) controller consists of two main parts: the first is fault detection and diagnosis (FDD) and the second is controller reconfiguration (CR). Systems subject to such abrupt failures are modeled as stochastic hybrid systems with variable‐structure. This paper deals with three challenging issues: design of the fault‐model set; estimation of hybrid multiple models; and stochastic MPC of hybrid multiple models. For the first issue, we propose a simple scheme for designing a fault model set based on random variables. For the second issue, we consider and select a fast and reliable FDD system applied to the above model set. Finally, we develop a stochastic MPC scheme for multiple model CR with soft switching signals based on the weighted probabilities of the outputs of different models. Simulations for the proposed FDMB controller are illustrated and analyzed. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Optimized treatment of fibromyalgia using system identification and hybrid model predictive control

The term adaptive intervention is used in behavioral health to describe individually tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health.     

任意切换时间下的二维线性混合系统的滑模控制

由于混合系统的复杂性,设计出能保证混合系统在任意切换时间下都能稳定的控制是比较困难的。为了突出滑模控制设计的思想,文章针对一类二维线性混合系统,提出通过确保混合系统实现滑动模的充分条件来保证系统的稳定性,并得到相应的控制律。仿真结果表明了该控制律的有效性。     

Stability analysis of a multi-model predictive control algorithm with application to control of chemical reactors

We study a stabilizing multi-model predictive control strategy for controlling nonlinear process at different operating conditions. The control algorithm is a receding horizon scheme with a quasi-infinite horizon objective function that has finite and infinite horizon cost components. The finite horizon cost consists of free input variables that direct the system towards a terminal region which contains the desired operating point. The infinite horizon cost has an upper bound and steers the system to the desired operating point. The system is represented by a sequence of piecewise linear models. Based on the condition of the system states, the sequence of piecewise linear models is updated and the controller’s objective function switches form quasi-infinite to infinite horizon objective function. This results in a hybrid control structure. A recent approach in the analysis of hybrid systems that uses multiple Lyapunov functions is employed in the stability analysis of the closed-loop system. The stabilizing hybrid control strategy is illustrated on two examples and their closed-loop stability properties are studied.     

Microcomputer based self-tuning and self-selecting controllers

Classical control system design techniques are extended to include cases with large parameter and state variations. New results on stability of adaptive gain control systems are obtained and a new method to design self-selecting controllers is presented.It is then shown that microcomputers are well suited for hybrid implementation of the resulting control systems.Several examples and a short survey on industrial applications are also given.     

Performance improvement of SISO linear control systems by hybrid state resetting and sector confinement of trajectories

Reset control techniques have been proposed to overcome fundamental limitations of linear controllers by means of their transformation into hybrid models that combine continuous flow and discrete jump dynamics. The hybrid nature in the control loop involves some difficulties when analyzing the performance of the controller and some drawbacks on the controller design related to the stability conditions. The technique that we propose is based on sector confined target dynamics of the continuous flow mode by means of the application of the discrete reset jumps. This behavior, in the error plane , is correlated with certain preferred sectors that lead to fast and over‐damped responses. The paper studies how to design a hybrid resetting version of a linear controller that achieves the required fast and over‐damped responses to arbitrary references. Copyright © 2016 John Wiley & Sons, Ltd.     

含正反馈振动主动控制系统的混合自适应控制

对于存在结构正反馈的振动主动控制系统,传统的基于有限冲击响应的自适应前馈控制器设计方法难以同时保证控制系统稳定与良好的控制性能.本文在分析正反馈对前馈控制系统影响的基础上,基于无限冲击响应控制器设计模式,提出一种结合前馈自适应控制器和反馈自适应控制器的混合自适应振动主动控制方法.其中前馈自适应控制器采用参考传感器采集到的扰动相关信号作为参考信号,反馈自适应控制器通过构建扰动的估计量作为参考信号,控制器参数更新采用Landau参数递推算法.以一典型的具有固有正反馈性质的机械振动系统为控制对象,给出了该混合自适应控制算法的详细推导过程以及稳定性和收敛性分析过程,得到了算法稳定与收敛的严格正实条件以及相应放松严格正实条件的要求.在此基础上,通过构建实时振动主动控制实验平台,针对多种振动扰动开展对比实验分析.相关实验结果验证了本文提出的混合自适应振动主动控制方法的可行性和有效性.     

A framework for hybrid model predictive control in mineral processing

Model Predictive Control (MPC) is an advanced technique for process control that has seen a significant and widespread increase in its use in the process industry since its introduction. In mineral processing, in particular, several applications of conventional MPC can be found for the individual processes of crushing, grinding, flotation, thickening, agglomeration, and smelting with varying degrees of success depending on the variables involved and the control objectives. Given the complexity of the processes normally found in mineral processing, there is also great interest in the design and development of advanced control techniques which aim to deal with situations that conventional controllers are unable to do. In this aspect, Hybrid MPC enables the representation of systems, incorporating logical variables, rules, and continuous dynamics. This paper firstly presents a framework for modeling and representation of hybrid systems, and the design and development of hybrid predictive controllers. Additionally, two application examples in mineral processing are presented. Results through simulation show that the control schemes developed under this framework exhibit a better performance when compared with conventional expert or MPC controllers, while providing a highly systematized methodology for the analysis, design, and development of hybrid MPC controllers.     

Direct data‐driven design of switching controllers

Switching linear models can be used to represent the behavior of hybrid, time‐varying, and nonlinear systems, while generally providing a satisfactory trade‐off between accuracy and complexity. Although several control design techniques are available for such models, the effect of modeling errors on the closed‐loop performance has not been formally evaluated yet. In this paper, a data‐driven synthesis scheme is thus introduced to design optimal switching controllers directly from data, without needing a model of the plant. In particular, the theory will be developed for piecewise affine controllers, which have proven to be effective in many real‐world engineering applications. The performance of the proposed approach is illustrated on some benchmark simulation case studies.     

Multi-input,multi-output flight control system design for the YF-16 using nonlinear QFT and pilot compensation

Nonlinear quantitative feedback theory (QFT) and pilot compensation techniques are used to design a 2 × 2 flight control system for the YF-16 aircraft over a large range of plant uncertainty. The design is based on numerical input-output time histories generated with a FORTRAN implemented nonlinear simulation of the YF-16. The first step of the design process is the generation of a set of equivalent linear time-invariant (LTI) plant models to represent the actual nonlinear plant. It has been proven that the solution to the equivalent plant problem is guaranteed to solve the original nonlinear problem. Standard QFT techniques are then used in the design synthesis based on the equivalent plant models. A detailed mathematical development of the method used to develop these equivalent LTI plant models is provided. After this inner-loop design, pilot compensation is developed to reduce the pilot's workload. This outer-loop design is also based on a set of equivalent LTI plant models. This is accomplished by modelling the pilot with parameters that result in good handling qualities ratings, and developing the necessary compensation to force the desired system responses.     

不确定线性时滞系统的一种混杂状态反馈保成本控制及优化设计方法

本文研究一类不确定线性时滞系统的混杂状态反馈保成本控制及优化设计问题.假设存在有限个备选的控制增益已知的控制器,并且其中任何单一的状态反馈控制器都不能镇定系统,基于单Lyapunov函数的方法,给出了混杂状态反馈保成本控制的充分条件及优化设计方案.当备选的控制增益未知时,利用多Lyapunov函数法,同样给出混杂状态反馈保成本控制的充分条件及相应的优化设计方法.最后用仿真验证了文中方法的有效性.     

基于TC1766的混合动力汽车整车控制器的开发

开发了一种并联式混合动力汽车的整车控制器,以英飞凌32位单片机TC1766为微控制器,阐述了各个功能模块的硬件实现以及系统电磁兼容设计,在排放实验室进行了车载整车功能和性能试验.试验表明开发的整车控制器具备良好的控制品质,可满足混合动力汽车的动力、经济和环保要求.     

An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.