811 research outputs found
Integrated Design and Implementation of Embedded Control Systems with Scilab
Embedded systems are playing an increasingly important role in control
engineering. Despite their popularity, embedded systems are generally subject
to resource constraints and it is therefore difficult to build complex control
systems on embedded platforms. Traditionally, the design and implementation of
control systems are often separated, which causes the development of embedded
control systems to be highly time-consuming and costly. To address these
problems, this paper presents a low-cost, reusable, reconfigurable platform
that enables integrated design and implementation of embedded control systems.
To minimize the cost, free and open source software packages such as Linux and
Scilab are used. Scilab is ported to the embedded ARM-Linux system. The drivers
for interfacing Scilab with several communication protocols including serial,
Ethernet, and Modbus are developed. Experiments are conducted to test the
developed embedded platform. The use of Scilab enables implementation of
complex control algorithms on embedded platforms. With the developed platform,
it is possible to perform all phases of the development cycle of embedded
control systems in a unified environment, thus facilitating the reduction of
development time and cost.Comment: 15 pages, 14 figures; Open Access at
http://www.mdpi.org/sensors/papers/s8095501.pd
Hardware/Software Codesign
The current state of the art technology in integrated circuits allows the incorporation of multiple processor cores and memory arrays, in addition to application specific hardware, on a single substrate. As silicon technology has become more advanced, allowing the implementation of more complex designs, systems have begun to incorporate considerable amounts of embedded software [3]. Thus it becomes increasingly necessary for the system designers to have knowledge on both hardware and software to make efficient design tradeoffs. This is where hardware/software codesign comes into existence
Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems
To exploit the power of modern heterogeneous multiprocessor embedded platforms on partitioned applications, the designer usually needs to efficiently map and schedule all the tasks and the communications of the application, respecting the constraints imposed by the target architecture. Since the problem is heavily constrained, common methods used to explore such design space usually fail, obtaining low-quality solutions. In this paper, we propose an ant colony optimization (ACO) heuristic that, given a model of the target architecture and the application, efficiently executes both scheduling and mapping to optimize the application performance. We compare our approach with several other heuristics, including simulated annealing, tabu search, and genetic algorithms, on the performance to reach the optimum value and on the potential to explore the design space. We show that our approach obtains better results than other heuristics by at least 16% on average, despite an overhead in execution time. Finally, we validate the approach by scheduling and mapping a JPEG encoder on a realistic target architecture
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