855 resultados para fpga, usb
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Gordon E. Moore, cofundador de Intel, predijo en una publicación del año 1965 que aproximadamente cada dos años se duplicaría el número de transistores presentes en un circuito integrado, debido a las cada vez mejores tecnologías presentes en el proceso de elaboración [1]. A esta ley se la conoce como Ley de Moore y su cumplimiento se ha podido constatar hasta hoy en día. Gracias a ello, con el paso del tiempo cada vez se presentan en el mercado circuitos integrados más potentes, con mayores prestaciones para realizar tareas cada vez más complejas. Un tipo de circuitos integrados que han podido evolucionar de forma importante son los dispositivos de lógica programable, circuitos integrados que permiten implementar sobre ellos las funciones lógicas deseadas. Hasta hace no muchos años, dichos dispositivos eran capaces de incorporar circuitos compuestos por unas pocas funciones lógicas, pero gracias al proceso de miniaturización predicho por la Ley de Moore, hoy en día son capaces de implementar circuitos tan complejos como puede ser un microprocesador; dichos dispositivos reciben el nombre de FPGA, siglas de Field Programmable Gate Array. El presente proyecto tiene como objetivo construir un marco de fotos digital con reloj y despertador programable, valiéndose para ello de la FPGA Cyclone II de Altera y una pantalla táctil de la casa Terasic. Con este fin, se documentará en primera instancia los dispositivos a utilizar con sus características y posibilidades que plantean, para pasar posteriormente al diseño de la aplicación y su implementación e integración en la placa para comprobar su correcto funcionamiento.
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Model Predictive Control (MPC) is increasingly being proposed for application to miniaturized devices, fast and/or embedded systems. A major obstacle to this is its computation time requirement. Continuing our previous studies of implementing constrained MPC on Field Programmable Gate Arrays (FPGA), this paper begins to exploit the possibilities of parallel computation, with the aim of speeding up the MPC implementation. Simulation studies on a realistic example show that it is possible to implement constrained MPC on an FPGA chip with a 25MHz clock and achieve MPC implementation rates comparable to those achievable on a Pentium 3.0 GHz PC. Copyright © 2007 International Federation of Automatic Control All Rights Reserved.
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New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.
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This paper presents the steps and the challenges for implementing analytical, physics-based models for the insulated gate bipolar transistor (IGBT) and the PIN diode in hardware and more specifically in field programmable gate arrays (FPGAs). The models can be utilised in hardware co-simulation of complex power electronic converters and entire power systems in order to reduce the simulation time without compromising the accuracy of results. Such a co-simulation allows reliable prediction of the system's performance as well as accurate investigation of the power devices' behaviour during operation. Ultimately, this will allow application-specific optimisation of the devices' structure, circuit topologies as well as enhancement of the control and/or protection schemes.
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Alternative and more efficient computational methods can extend the applicability of model predictive control (MPC) to systems with tight real-time requirements. This paper presents a system-on-a-chip MPC system, implemented on a field-programmable gate array (FPGA), consisting of a sparse structure-exploiting primal dual interior point (PDIP) quadratic program (QP) solver for MPC reference tracking and a fast gradient QP solver for steady-state target calculation. A parallel reduced precision iterative solver is used to accelerate the solution of the set of linear equations forming the computational bottleneck of the PDIP algorithm. A numerical study of the effect of reducing the number of iterations highlights the effectiveness of the approach. The system is demonstrated with an FPGA-in-the-loop testbench controlling a nonlinear simulation of a large airliner. This paper considers many more manipulated inputs than any previous FPGA-based MPC implementation to date, yet the implementation comfortably fits into a midrange FPGA, and the controller compares well in terms of solution quality and latency to state-of-the-art QP solvers running on a standard PC. © 1993-2012 IEEE.
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A field programmable gate array (FPGA)-based predictive controller for a spacecraft rendezvous manoeuvre is presented. A linear time varying prediction model is used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of manoeuvres. The resulting constrained optimisation problems are solved using a primal dual interior point algorithm. The majority of the computational demand is in solving a set of linear equations at each iteration of this algorithm. To accelerate this operation, a custom circuit is implemented, using a combination of Mathworks HDL Coder and Xilinx System Generator for DSP, and used as a peripheral to a MicroBlaze soft core processor. The system is demonstrated in closed loop by linking the FPGA with a simulation of the plant dynamics running in Simulink on a PC, using Ethernet. © 2013 EUCA.
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z
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Submitted by zhangdi (zhangdi@red.semi.ac.cn) on 2009-04-13T11:45:31Z