18,376 research outputs found
Resource Management for Control Tasks Based on the Transient Dynamics of Closed-Loop Systems
This paper presents a resource management strategy for control tasks that maximizes control performance within the available resources by readjusting the task periods at run-time. A feedback scheduler is used to determine on-line the optimal task periods considering the response over a finite time horizon of the plants controlled by arbitrary linear control laws. We show how this problem can be expressed as an optimization problem, where the objective function relates the sampling periods to the transient responses of the controlled plants, and where restrictions are based on EDF schedulability constraints. For the general case, the solution of the optimization problem is computationally expensive, and thus, an approximate procedure to be executed on-line has been developed. We present simulation results that validate the presented approach
A Developmental Organization for Robot Behavior
This paper focuses on exploring how learning and development can be structured in synthetic (robot) systems. We present a developmental assembler for constructing reusable and temporally extended actions in a sequence. The discussion adopts the traditions
of dynamic pattern theory in which behavior
is an artifact of coupled dynamical systems
with a number of controllable degrees of freedom. In our model, the events that delineate
control decisions are derived from the pattern
of (dis)equilibria on a working subset of sensorimotor policies. We show how this architecture can be used to accomplish sequential
knowledge gathering and representation tasks
and provide examples of the kind of developmental milestones that this approach has
already produced in our lab
Fuzzy Feedback Scheduling of Resource-Constrained Embedded Control Systems
The quality of control (QoC) of a resource-constrained embedded control
system may be jeopardized in dynamic environments with variable workload. This
gives rise to the increasing demand of co-design of control and scheduling. To
deal with uncertainties in resource availability, a fuzzy feedback scheduling
(FFS) scheme is proposed in this paper. Within the framework of feedback
scheduling, the sampling periods of control loops are dynamically adjusted
using the fuzzy control technique. The feedback scheduler provides QoC
guarantees in dynamic environments through maintaining the CPU utilization at a
desired level. The framework and design methodology of the proposed FFS scheme
are described in detail. A simplified mobile robot target tracking system is
investigated as a case study to demonstrate the effectiveness of the proposed
FFS scheme. The scheme is independent of task execution times, robust to
measurement noises, and easy to implement, while incurring only a small
overhead.Comment: To appear in International Journal of Innovative Computing,
Information and Contro
Neural Feedback Scheduling of Real-Time Control Tasks
Many embedded real-time control systems suffer from resource constraints and
dynamic workload variations. Although optimal feedback scheduling schemes are
in principle capable of maximizing the overall control performance of
multitasking control systems, most of them induce excessively large
computational overheads associated with the mathematical optimization routines
involved and hence are not directly applicable to practical systems. To
optimize the overall control performance while minimizing the overhead of
feedback scheduling, this paper proposes an efficient feedback scheduling
scheme based on feedforward neural networks. Using the optimal solutions
obtained offline by mathematical optimization methods, a back-propagation (BP)
neural network is designed to adapt online the sampling periods of concurrent
control tasks with respect to changes in computing resource availability.
Numerical simulation results show that the proposed scheme can reduce the
computational overhead significantly while delivering almost the same overall
control performance as compared to optimal feedback scheduling.Comment: To appear in International Journal of Innovative Computing,
Information and Contro
Technology for the Future: In-Space Technology Experiments Program, part 2
The purpose of the Office of Aeronautics and Space Technology (OAST) In-Space Technology Experiments Program In-STEP 1988 Workshop was to identify and prioritize technologies that are critical for future national space programs and require validation in the space environment, and review current NASA (In-Reach) and industry/ university (Out-Reach) experiments. A prioritized list of the critical technology needs was developed for the following eight disciplines: structures; environmental effects; power systems and thermal management; fluid management and propulsion systems; automation and robotics; sensors and information systems; in-space systems; and humans in space. This is part two of two parts and contains the critical technology presentations for the eight theme elements and a summary listing of critical space technology needs for each theme
Control-theoretic dynamic voltage scaling for embedded controllers
For microprocessors used in real-time embedded systems, minimizing power
consumption is difficult due to the timing constraints. Dynamic voltage scaling
(DVS) has been incorporated into modern microprocessors as a promising
technique for exploring the trade-off between energy consumption and system
performance. However, it remains a challenge to realize the potential of DVS in
unpredictable environments where the system workload cannot be accurately
known. Addressing system-level power-aware design for DVS-enabled embedded
controllers, this paper establishes an analytical model for the DVS system that
encompasses multiple real-time control tasks. From this model, a feedback
control based approach to power management is developed to reduce dynamic power
consumption while achieving good application performance. With this approach,
the unpredictability and variability of task execution times can be attacked.
Thanks to the use of feedback control theory, predictable performance of the
DVS system is achieved, which is favorable to real-time applications. Extensive
simulations are conducted to evaluate the performance of the proposed approach.Comment: Accepted for publication in IET Computers and Digital Techniques.
doi:10.1049/iet-cdt:2007011
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