基于DVS技术的性能感知反馈调度算法

传统DVS算法在能量管理方面没有考虑实际系统性能的需求,这在一定意义上限制了其节能效果．针对这一问题,提出一种基于DVS技术的性能感知反馈调度算法．在反馈调度器中,分别采用DVS技术和模糊控制技术设计CPU电压调节模块和控制任务周期调节模块,实现对系统CPU速率和控制任务采样周期的动态调节．通过与基于固定采样周期的DVS反馈调度算法进行对比,结果表明该算法在保证系统控制性能的同时进一步降低了系统能耗．     

ABR流量控制中的变结构控制器

自适应比特(available bit rate,简称ABR)业务的流量控制是ATM网络中一种有效的拥塞控制机制和流量管理手段.在高速的ATM网络中,算法的简洁性在很大程度上决定着交换机的性能.尽管二进制ABR流量控制的简洁性具有相当大的吸引力,但标准的EFCI算法控制的队列长度和允许信元速率(allowed cell rate,简称ACR)却容易出现大幅振荡的现象,这势必会降低链路的利用率,严重影响交换机的性能.进而又有了相对复杂却有效的显式速率反馈机制.在此研究中,以已有的ABR流量控制模型为基础,应用概率拥塞判定机制,并借助鲁棒控制理论中滑模变结构控制器的设计方法,为ABR流量控制设计了一种新的二进制算法,避免了标准EFCI算法中非线性环节诱发的自激振荡,这对于充分发挥二进制流控算法的简洁性以及优化交换机的性能是极为有利的.仿真实验表明:二进制流量控制中的滑模变结构算法大幅度地抑制了ACR和队列的振荡,平滑了由此而引入的时延抖动,为实现ATM网络中的服务质量提供了可靠的实现机制.     

Providing QoS with the Deficit Table Scheduler

A key component for networks with Quality of Service (QoS) support is the egress link scheduling algorithm. An ideal scheduling algorithm implemented in a high-performance network with QoS support should satisfy two main properties: good end-to-end delay and implementation simplicity. Table-based schedulers try to offer a simple implementation and good latency bounds. Some of the latest proposals of network technologies, like Advanced Switching and InfiniBand, include in their specifications one of these schedulers. However, these table-based schedulers do not work properly with variable packet sizes, as is usually the case in current network technologies. We have proposed a new table-based scheduler, which we have called Deficit Table (DTable) scheduler, that works properly with variable packet sizes. Moreover, we have proposed a methodology to configure this table-based scheduler in such a way that it permits us to decouple the bounding between the bandwidth and latency assignments. In this paper, we thoroughly review the provision of QoS with the DTable scheduler and our configuration methodology, and evaluate the performance of our proposals in a multimedia scenario. Simulation results show that our proposals are able to provide a similar latency performance than more complex scheduling algorithms. Moreover, we show the advantages of our decoupling configuration methodology over the usual ways of configuring this kind of table-based schedulers.     

Optimal LQ feedforward tracking with preview: Practical design for rigid body motion control

For reference-tracking motion control, preview-based linear quadratic (LQ) design methods provide an effective means to balance tracking performance with available actuation capacity. This paper considers a control structure for which the optimal feedforward controller is independent of the feedback controller. In this way, explicit implementation formulas for feedforward controllers are derived that can be applied to a range of rigid-body motion systems. Key aspects of the optimal LQ solutions are identified, particularly how the choice of design weightings affect steady-state error for polynomial tracking. A redesign procedure for finite preview-time is proposed that preserves exact polynomial tracking properties and control bandwidth of the optimal solutions. Comparative experimental results are presented for a motor-driven linear motion stage.     

Experimental Assessment of the Period Calibration Method: A Case Study

In this paper we present an experimental evaluation of the period calibration method (PCM) which was developed in Gerber et al. (1994, 1995) as a systematic design methodology for real-time systems. The objective of this experimental study is to assess design alternatives integrated into the method and their performance implication on resultant systems built via the PCM. Such design alternatives include scheduling jitter, sensor-to-output latency, intertask communication schemes, and system utilization. For this study, we have chosen a computerized numerical control (CNC) machine as our target real-time system, and built a realistic controller and a plant simulator. We show the detailed development process of the CNC controller and report its performance. The performance results were extracted from a controlled series of more than hundred test controllers obtained by varying four test variables. This study unveils several weaknesses of the PCM: (1) the communication scheme built into PCM incurs a large latency though average sensor-to-output latency is one of the most dominating factors in determining control quality; (2) scheduling jitter is taken seriously in PCM though its effect appears only when average sensor-to-output latency is sufficiently small; (3) loop processing periods are not properly optimized for control quality though they are another dominating factor of performance; and (4) transient overloads are not considered at all in PCM, even though they can seriously damage the performance of a system. Based on these results, we propose a new communication scheme and a transient overload handling technique for the improved period calibration method.     

A design technique for fast sampled-data nonlinear model predictive control with convergence and stability results

ABSTRACT

In this study, a sampled-data nonlinear model predictive control scheme is developed. The control algorithm uses a prediction horizon with variable length, a terminal constraint set, and a feedback controller defined on this set. Following a suboptimal solution strategy, a defined number of steps of an iterative optimisation routine improve the current input trajectory at each sampling point. The value of the objective function monotonically decreases and the state converges to a target set. A discrete-time formulation of the algorithm and a discrete-time design model ensure high computational efficiency and avoid an ad hoc quasi-continuous implementation. This design technique for a fast sampled-data nonlinear model predictive control algorithm is the main contribution of the paper. Based on a benchmark control problem, the performance of the developed control algorithm is assessed against state-of-the-art nonlinear model predictive control methods available in the literature. This assessment demonstrates that the developed control algorithm stabilises the system with very low computational effort. Hence, the algorithm is suitable for real-time control of fast dynamical systems.     

模糊反馈控制实时调度算法

为了解决模糊不确定任务集在不可预测环境下的动态抢占调度问题,应用模糊规则和模糊调度理论,提出一个基于模糊反馈控制的调度算法,并建立相应的调度架构.该架构由基本调度器和模糊反馈控制两部分组成.用模糊调度算法作为基本调度器的调度算法,将任务集按不同优先级等级进行划分,优先级等级高的任务优先调度,从而使得更多的重要任务得到调度;模糊控制器与任务流调节策略一起构成模糊反馈控制部分.仿真结果表明,模糊反     

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.     

Robust MPC for systems with output feedback and input saturation

In this work, it is proposed an MPC control algorithm with proved robust stability for systems with model uncertainty and output feedback. It is assumed that the operating strategy is such that system inputs may become saturated at transient or steady state. The developed strategy aims at the case in which the controller performs in the output-tracking scheme following an optimal set point that is provided by an upper optimization layer of the plant control structure. In this case, the optimal operating point usually lies at the boundary of the region where the input is defined. Assuming that the system remains stabilizable in the presence of input saturation, the design of the robust controller is performed off-line and an on-line implementation strategy is proposed. At each sampling step, a sub optimal control law is obtained by combining control configurations that correspond to particular subsets of available manipulated inputs. Stability of the closed-loop system is forced by considering in the off-line step of the controller design, a state contracting restriction for the closed-loop system. To produce an offset free controller and to attend the case of unknown steady state, the method is developed for a state-space model in the incremental form. The method is illustrated with simulation examples extracted from the process industry.     

Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

In this note, we revisit the problem of scheduling stabilizing control tasks on embedded processors. We start from the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant. This controller has for objective guaranteeing that (control unrelated) software tasks meet their deadlines and that stabilizing control tasks asymptotically stabilize the plant. We investigate a simple event-triggered scheduler based on this feedback paradigm and show how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.     

Robust model predictive control with guaranteed setpoint tracking

In this paper a novel robust model predictive control (RMPC) algorithm is proposed, which is guaranteed to stabilize any linear time-varying system in a given convex uncertainty region while respecting state and input constraints. Moreover, unlike most existing RMPC algorithms, the proposed algorithm is guaranteed to remove steady-state offset in the controlled variables for setpoints (possibly) different from the origin when the system is unknown linear time-invariant. The controller uses a dual-mode paradigm (linear control law plus free control moves to reach an appropriate invariant region), and the key step is the design of a robust linear state feedback controller with integral action and the construction of an appropriate polyhedral invariant region in which this controller is guaranteed to satisfy the process constraints. The proposed algorithm is efficient since the on-line implementation only requires one to solve a convex quadratic program with a number of decision variables that scale linearly with the control horizon. The main features of the new control algorithm are illustrated through an example of the temperature control of an open-loop unstable continuous stirred tank reactor.     

Feedback–Feedforward Scheduling of Control Tasks

A scheduling architecture for real-time control tasks is proposed. The scheduler uses feedback from execution-time measurements and feedforward from workload changes to adjust the sampling periods of the control tasks so that the combined performance of the controllers is optimized. The performance of each controller is described by a cost function. Based on the solution to the optimal resource allocation problem, explicit solutions are derived for linear and quadratic approximations of the cost functions. It is shown that a linear rescaling of the nominal sampling frequencies is optimal for both of these approximations. An extensive inverted pendulum example is presented, where the performance obtained with open-loop, feedback, combined feedback and feedforward scheduling, and earliest-deadline first scheduling are compared. The performance under earliest-deadline first scheduling is explained by studying the behavior of periodic tasks under overload conditions. It is shown that the average values of the sampling periods equal the nominal periods, rescaled by the processor utilization.     

Model-based periodic event-triggered stabilization for continuous-time stochastic nonlinear systems

In this paper, we investigate a model-based periodic event-triggered control framework for continuous-time stochastic nonlinear systems. In this framework, an auxiliary approximate discrete-time model of stochastic nonlinear systems is constructed in the controller module, which is utilized not only to design a discrete-time controller but also as a state predictor within trigger intervals. This discrete controller design approach, the strategy of state prediction, and the periodic detection strategy for the trigger rule not only provide a manner of more direct and easier implementation on the digital platform but also effectively reduce the communication load while a satisfactory control performance is maintained. Additionally, the mean-square exponentially stabilization for continuous-time stochastic nonlinear systems is achieved, in which a guideline for determining the maximum admissible sampling period is provided and the periodic event trigger rule is designed. The final numerical simulation also supports the effectiveness of our proposed framework.     

ATM网络拥塞控制中PID控制器的设计

自适应比特（ABR）业务的流量控制是ATM网络中一种有效的拥塞控制机制和流量管理手段。在大规模的高速网络中，算法的简洁性对优化交换机的性能是至关重要的。尽管二进制ABR流量控制的简洁性具有相当的吸引力，但显式前向拥塞标识（Explicit Forward Congestion Indication,EFCI)算法控制的队列长度和允许信元速率（Allowed Cell Rate,ACR)大幅振荡，降低了链路利用率，严重的影响了交换机的性能，为此有了相对复杂却有效的显式速率反馈机制，在该文中，引入了拥塞的概率判定机制，并运用经典控制理论为拥塞判定概率的实量更新设计了线性的PID控制器，避免了非线性的控制规律可能诱发的系统自激振荡，在PID控制器的参数整定上，因为使用常用处受到限制，进而给出了一种基于确定稳定裕度的参数整定方法，仿真试验表明：二进制流量控制中的PID算法在保持了算法简洁性的前提下，大幅度地抑制了ACR和队列长度的振荡，提高了链路利用率，减小了队列系统引入的时延抖动，为保证ATM网络中的服务质量（Quality of Service,Qos)提供了必要的技术支持。     

Multirate sampled‐data stabilization for a class of low‐order lower‐triangular nonlinear systems

This paper investigates the problem of sampled‐data controller design for a class of lower‐triangular systems in the p‐normal form (0<p<1). A multirate digital feedback control scheme is proposed to achieve the global strong stabilization of the sampled‐data closed‐loop system under some assumptions. In the design of the controller, the input‐Lyapunov matching strategy and multirate control approach are combined to obtain better stabilizing performance. Unlike the design method based on the approximate discrete‐time model, our controller is obtained from the exact discrete‐time equivalent model, which does not need to be computed completely. The approximate multirate digital controllers are proved to be effective in the practical implementation. It is shown that, compared with the emulated control scheme, our controller may provide faster decrease of Lyapunov function for each subsystem. This will lead to allow large sampling periods. An illustrative example is provided to verify the effectiveness of the proposed control scheme.     

网络控制系统中基于模糊反馈的消息调度

在网络带宽受限的情况下, 综合考虑了系统响应的误差和误差变化率, 设计了一个共享通信网络的模糊反馈调度器. 该调度器采用模糊最大优先调度算法对网络消息发送的优先级进行动态调整. 同时定义了一种归一化控制质量衡量指标来评价多回路系统的控制性能. 在此评价方法下, 对三种不同调度算法在不同随机时延序列下进行了仿真比较. 结果表明本文提出的调度算法优化了系统的控制性能, 并在不确定运行环境中具有更好的适应性.     

Feedback EDF Scheduling of Real-Time Tasks Exploiting Dynamic Voltage Scaling

Many embedded systems are constrained by limits on power consumption, which are reflected in the design and implementation for conserving their energy utilization. Dynamic voltage scaling (DVS) has become a promising method for embedded systems to exploit multiple voltage and frequency levels and to prolong their battery life. However, pure DVS techniques do not perform well for systems with dynamic workloads where the job execution times vary significantly. In this paper, we present a novel approach combining feedback control with DVS schemes targeting hard real-time systems with dynamic workloads. Our method relies strictly on operating system support by integrating a DVS scheduler and a feedback controller within the earliest-deadline-first (EDF) scheduling algorithm. Each task is divided into two portions. The objective within the first portion is to exploit frequency scaling for the average execution time. Static and dynamic slack is accumulated for each task with slack-passing and preemption handling schemes. The objective within the second portion is to meet the hard real-time deadline requirements up to the worst-case execution time following a last-chance approach. Feedback control techniques make the system capable of selecting the right frequency and voltage settings for the first portion, as well as guaranteeing hard real-time requirements for the overall task. A feedback control model is given to describe our feedback DVS scheduler, which is used to analyze the system's stability. Simulation experiments demonstrate the ability of our algorithm to save up to 29% more energy than previous work for task sets with different dynamic workload characteristics. This work was supported in part by NSF grants CCR-0208581, CCR-0310860 and CCR-0312695. Preliminary versions of parts of this work appeared in the ACM SIGPLAN Joint Conference Languages, Compilers, and Tools for Embedded Systems (LCTES'02) and Software and Compilers for Embedded Systems (SCOPES'02) (Dudani et al., 2002), in the Workshop on Compilers and Operating Systems for Low Power 2002 (Zhu and Mueller, 2002) and in the IEEE Real-Time Embedded Technology and Applications Symposium 2004 (Zhu and Mueller, 2004a).     

Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties

This paper addresses a three-dimensional (3D) path following control problem for underactuated autonomous underwater vehicle (AUV) subject to both internal and external uncertainties. A two-layered framework synthesizing the 3D guidance law and heuristic fuzzy control is proposed to achieve robust adaptive following along a predefined path. In the first layer, a 3D guidance controller for underactuated AUV is presented to guarantee the stability of path following in the kinematics stage. In the second layer, a heuristic adaptive fuzzy algorithm based on the guidance command and feedback linearization Proportional-Integral-Derivative (PID) controller is developed in the dynamics stage to account for the nonlinear dynamics and system uncertainties, including inaccuracy modelling parameters and time-varying environmental disturbances. Furthermore, the sensitivity analysis of the heuristic fuzzy controller is presented. Against most existing methods for 3D path following, the proposed robust fuzzy control scheme reduces the design and implementation costs of complicated dynamics controller, and relaxes the knowledge of the accuracy dynamics modelling and environmental disturbances. Finally, numerical simulation results validate the effectiveness of the proposed control framework and illustrate the outperformance of the proposed controller as well.     

Internet拥塞控制系统校正控制器的一种新的设计方法

当前Internet拥塞控制系统中,作为闭环拥塞控制系统的校正控制器,采用了AQM(Active Queue Management)控制器技术;AQM控制器中通常采用RED(Random Early Detection)算法,但RED算法存在一系列缺点;文章在校正控制器的设计中,采用状态反馈控制算法,以提高Internet拥塞控制系统的控制性能。内容包括:被控制系统模型、状态反馈控制器设计及状态变量测量等问题;最后通过NS2平台上的仿真计算,验证了所提出方法在动态性能上优于RED算法。     

实时控制任务的模糊反馈调度系统研究

分析了实时控制任务的控制性能在不同控制阶段与处理器利用率需求间的关系,提出一种实时控制任务的模糊反馈调度系统.模糊控制器通过监测实时控制任务的误差及其变化率,查询模糊决策表,动态决定任务的优先级,反馈调度器根据优先级分配任务的利用率.仿真结果表明，在计算资源有限时，该方法能有效改善实时控制任务的控制性能.