Improving quality-of-control using flexible timing constraints: metric and scheduling

Martí, Pau; Fuertes, Josep M.; Fohler, Gerhard; Ramamritham, Krithi

doi:10.1109/real.2002.1181565

Cited by 55 publications

(56 citation statements)

References 10 publications

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“…In figure 4 and at t = 2s, instead of reserving half of the network bandwidth to subsystem 1, which is very close to the equilibrium, the adaptive scheduling algorithm uses these resources to achieve a quicker and better stabilization of subsystem 2. These results are is accordance with those of (Martí et al, 2002), where the empirical study of the relationship between resource allocation and control performance was undertaken. 6.…”

Section: A Numerical Examplesupporting

confidence: 92%

Model Predictive Control of Systems With Communication Constraints

Gaïd

Çela

2005

IFAC Proceedings Volumes

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This paper addresses the problem of the on-line scheduling of a limited communication resource in order to optimize the control performance. A multivariable linear system with communication constraints is modeled in the Mixed Logical Dynamical (MLD) framework. The system is controlled using a Model Predictive Controller (MPC), which computes, at each sampling period, the appropriate control values and network allocation. The performance of the controlled system is evaluated using a Linear-Quadratic cost function. At each step, the MPC needs to solve an optimization problem, including logic constraints. The translation of this problem into the Mixed Integer Quadratic Programming (MIQP) formulation is described. Finally, using a numerical example, the relationship between the state variables of the plant and the resultant allocation of the communication resource is investigated.

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Section: A Numerical Examplesupporting

confidence: 92%

Model Predictive Control of Systems With Communication Constraints

Gaïd

Çela

2005

IFAC Proceedings Volumes

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“…In reality, as illustrated in [3], [4], the quality of control is also dependent on the dynamical state of the controlled system (in equilibrium, in transient state). In this paper, instead of using feedback from execution times measures, the plant state information is used to dispatch the available computing resources.…”

Section: Related Workmentioning

confidence: 99%

“…This corresponds to the use of periodic sampling, which on the one hand simplifies the control design problem, but on the other hand leads to an unnecessary usage of some computational resources. In fact, a control task that is close to the equilibrium needs less computing resources than another one which is severely disturbed [3]- [5]. Similarly, the real-time scheduling design of control tasks is based on their worst-case execution time.…”

mentioning

confidence: 99%

Optimal Real-Time Scheduling of Control Tasks With State Feedback Resource Allocation

Gaïd

Çela

Hamam

2009

IEEE Trans. Contr. Syst. Technol.

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Abstract-This paper proposes a new approach for the optimal integrated control and real-time scheduling of control tasks. First, the problem of the optimal integrated control and nonpreemptive off-line scheduling of control tasks in the sense of the H2 performance criterion is addressed. It is shown that this problem may be decomposed into two sub-problems. The first sub-problem aims at finding the optimal non-preemptive off-line schedule, and may be solved using the branch and bound method. The second sub-problem uses the lifting technique to determine the optimal control gains, based on the solution of the first sub-problem. Second, an efficient on-line scheduling algorithm is proposed. This algorithm, called Reactive Pointer Placement (RPP) scheduling algorithm, uses the plant state information to dispatch the computational resources in a way that improves control performance. Control performance improvements as well as stability guarantees are formally proven. Finally, simulations as well as experimental results are presented in order to illustrate the effectiveness of the proposed approach.

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“…FC-ORB is particularly useful for DRE applications that are amenable to rate adaptation such as digital feedback control systems (Marti et al, 2002;Seto et al, 1996), monitoring systems (Zhao et al, 2001), and multimedia (Brandt et al, 1998). In these systems, task rates can be adjusted without causing system failure.…”

Section: A U T H O R ' S P E R S O N a L C O P Ymentioning

confidence: 99%

“…Second, the rate of a task T i may be dynamically adjusted within a range [R min,i , R max,i ]. This assumption is based on the fact that the task rates in many DRE applications (e.g., digital control (Marti et al, 2002;Seto et al, 1996), sensor update, and multimedia (Brandt et al, 1998)) can be dynamically adjusted without causing system failure. A task running 1 FC-ORB can be extended to support a more general task model in which a task is composed of a graph of subtasks (Liu, 2000 …”

mentioning

confidence: 99%

FC-ORB: A robust distributed real-time embedded middleware with end-to-end utilization control

Wang

Chen

et al. 2007

Journal of Systems and Software

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A key challenge for distributed real-time and embedded (DRE) middleware is maintaining both system reliability and desired realtime performance in unpredictable environments where system workload and resources may fluctuate significantly. This paper presents FC-ORB, a real-time Object Request Broker (ORB) middleware that employs end-to-end utilization control to handle fluctuations in application workload and system resources. The contributions of this paper are three-fold. First, we present a novel utilization control service that enforces desired CPU utilization bounds on multiple processors by adapting the rates of end-to-end tasks within user-specified ranges. Second, we describe a set of middleware-level mechanisms designed to support end-to-end tasks and distributed multi-processor utilization control in a real-time ORB. Finally, we present extensive experimental results on a Linux testbed. Our results demonstrate that our middleware can maintain desired utilizations in face of uncertainties and variations in task execution times, resource contentions from external workloads, and permanent processor failure. FC-ORB demonstrates that the integration of utilization control, end-to-end scheduling, and fault-tolerance mechanisms in DRE middleware is a promising approach for enhancing the robustness of DRE applications in unpredictable environments.

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Improving quality-of-control using flexible timing constraints: metric and scheduling

Cited by 55 publications

References 10 publications

Model Predictive Control of Systems With Communication Constraints

Model Predictive Control of Systems With Communication Constraints

Optimal Real-Time Scheduling of Control Tasks With State Feedback Resource Allocation

FC-ORB: A robust distributed real-time embedded middleware with end-to-end utilization control

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