This paper describes implementation of the Dynamic Matrix Control (DMC) algorithm performed on an Altera field programmable gate array (FPGA) with the Cyclone IV chip. The DMC algorithm is implemented in its analytica...
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ISBN:
(纸本)9783319606996
This paper describes implementation of the Dynamic Matrix Control (DMC) algorithm performed on an Altera field programmable gate array (FPGA) with the Cyclone IV chip. The DMC algorithm is implemented in its analytical (explicit) version which requires computationally simple matrix and vector operations in real time, no on-line optimisation is necessary. The test-bench application is prepared for fast comparison between C and HDL versions of code. A large number of independent logic cells can provide multi-parallel operations to achieve very fast operations. As a result, the algorithm may be used for controlling very fast dynamic processes characterised by sampling periods of millisecond order. Preliminary results of real experiments are demonstrated. The discussed control structure provides possibility to fast change of algorithm.
This paper presents the design of a system that is aimed to provide a flexible, portable and low cost solution for optical fiber based sensor systems. The field programmable gate array (FPGA) provides the digital logi...
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ISBN:
(纸本)9781538604496
This paper presents the design of a system that is aimed to provide a flexible, portable and low cost solution for optical fiber based sensor systems. The field programmable gate array (FPGA) provides the digital logic to implement the system and ability to reconfigure the system operation. It aims to support different optical fiber sensing requirements by the ability to reconfigure the digital circuitry used. It is therefore a hardware configured alternative to a software programmed processor based approach. The work discussed in this paper focuses on the architecture of the FPGA based system with additional circuitry to implement the light source using a light emitting diode (LED), sensor signal sampling using a photodiode and the digital functions implemented using the Xilinx Artix-7 FPGA. The system also includes serial communications to an external computer that allows the system to be used as part of a larger sensor network. In this paper, system control and sensor data visualization on a personal computer (PC) is undertaken using the Python open source programming language.
Real-time simulation of dynamic vehicle system models is essential to facilitate advances in operator and hardware in the loop simulation and virtual prototyping. Real-time virtual reality-based simulation enables use...
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ISBN:
(纸本)9780791849088
Real-time simulation of dynamic vehicle system models is essential to facilitate advances in operator and hardware in the loop simulation and virtual prototyping. Real-time virtual reality-based simulation enables users to visualize and perceive the effect of their actions during the simulation. As model complexity is increased to improve the model fidelity, the computational requirements will also increase, thus increasing the challenge to meet real-time constraints. A distributed simulator architecture was developed for off-road vehicle dynamic models and 3D graphics visualization to distribute the overall computational load across multiple computational platforms. This architecture consisted of three major components: a dynamic model simulator, a virtual reality simulator, and an interface to controller and input hardware devices. The dynamic model simulator component was developed using Matlab/Simulink Real Time Workshop on a PC and also using field programmable gate arrays (FPGA), which offered a highly parallel hardware platform. The simulator architecture reduced the computational load to an individual platform and increased the real-time simulation capability with complex off-road vehicle system models and controllers. The architecture was used to develop, simulate and visualize a tractor and towed implement steering dynamics model. The model also included a steering valve subsystem which contained very high frequency hydraulic dynamics and required 10 mu s integration time step for numerical stability. The real-time simulation goal was not achievable for the model with this level of complexity when the PC-based simulator was used. However, the FPGA-based simulator achieved a real-time goal taking only 2 mu s to complete one integration time step.
The objective of this paper is to describe an implementation of a Dynamic Matrix Control (DMC) algorithm for a field programmable gate array (FPGA). The DMC algorithm is implemented in a universal version for multiple...
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The objective of this paper is to describe an implementation of a Dynamic Matrix Control (DMC) algorithm for a field programmable gate array (FPGA). The DMC algorithm is implemented in a universal version for multiple-input multiple-output dynamic processes. The results of real experiments are presented in which the DE2i-150 development board produced by Terasic with Intel Cyclone IV GX chip is used. As the controlled process a laboratory stand especially developed for this work is used, which is a dynamic system with two manipulated inputs and two controlled outputs. The implemented DMC controller is very fast, it may be used for controlling processed which need sampling periods of a millisecond order. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
Proportional Integral Derivative (PID) controller is the most preferable controller in industries that does not require precise analytical model of the system to be controlled. Implementation of PID controllers has go...
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ISBN:
(纸本)9781424434503
Proportional Integral Derivative (PID) controller is the most preferable controller in industries that does not require precise analytical model of the system to be controlled. Implementation of PID controllers has gone through several stages of evolution from the early mechanical and pneumatic designs to the microprocessor based systems. Recently "field programmable gate array" has become an alternative solution for the realization of Digital PID controllers. This work is aimed at the implementation of serial, parallel and mixed PID controller architectures using FPGA. The digital PID so designed is based essentially in architectures including multipliers, adders and some other logic circuits.
A detailed methodology for implementing a fully connected (FC) deep neural network (DNN) and convolutional neural network (CNN) inference system on a field programming gatearray (FPGA) is presented. Minimal computati...
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A detailed methodology for implementing a fully connected (FC) deep neural network (DNN) and convolutional neural network (CNN) inference system on a field programming gatearray (FPGA) is presented. Minimal computational units are used for the DNN. For the CNN, systolic array (SA) architecture endowed with parallel processing potential is utilized. Algorithmic analysis determines the optimum memory requirement for the fixed point trained parameters. The size of the trained parameters and the available memory on the target FPGA device govern the choice of on-chip memory to utilize. Experimental results indicate that the choice of block over distributed memory saves approximate to 62% look-up-tables (LUTs) for the DNN ([784-512-512-10]), and the choice of distributed over block memory saves approximate to 30% block random access memory (BRAM) for the LeNet-5 CNN unit. This study provides insights for developing FPGA-based digital systems for applications requiring DNN and CNN.
Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use o...
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Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use of reconfigurable hardware [field programmable gate arrays (FPGAs)], and relevant research has produced quite fascinating results, in both the accuracy of the detection algorithms as well as the performance in terms of frames per second (fps) for use in embedded smart camera systems. Detecting objects in images, however, is a daunting task and often involves hardware-inefficient steps, both in terms of the datapath design and in terms of input/output and memory access patterns. We present how a visual-feature-directed search cascade composed of motion detection, depth computation, and edge detection, can have a significant impact in reducing the data that needs to be examined by the classification engine for the presence of an object of interest. Experimental results on a Spartan 6 FPGA platform for face detection indicate data search reduction of up to 95%, which results in the system being able to process up to 50 1024 x 768 pixels images per second with a significantly reduced number of false positives. (C) 2016 SPIE and IS&T
Harvesting solar energy through photovoltaic (PV) power systems plays an important role in achieving the goal of carbon neutrality. However, the early microdefects in PV cells considerably affect the efficiencies of P...
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Harvesting solar energy through photovoltaic (PV) power systems plays an important role in achieving the goal of carbon neutrality. However, the early microdefects in PV cells considerably affect the efficiencies of PV power systems. In addition, the growing number of PV power systems require more efficient and economic detection methods to ensure the long-term efficiency of PV power systems. To address this problem, recent state-of-the-art methods have attempted to use a convolutional neural network (CNN) model. However, these methods involve large amounts of parameters and require too many calculations, considerably affecting the efficiency, economy, and flexibility in real applications. In this work, we propose a lightweight dual -flow defect detection network (DDDN) and accelerate it with a field programmable gate array (FPGA) based on the developed dual-flow parallel computing architecture (DPCA). The DDDN can accurately detect early microdefects in PV cells with low calculations and storage costs, while the DPCA optimizes the data access and computation process to improve detection efficiency and reduce power consumption. Benefiting from the designed DDDN and DPCA, the proposed system achieves a high detection accuracy (88.26%), low power consumption (22 W), and competitive detection efficiency, making it more suitable than previous methods for ensuring the long-term efficiency of PV power systems.
Numerical models of holograms are available but their evaluation is a very computationally intensive task. We present an acceleration algorithm for optical field synthesis suitable for the reduced occlusion method of ...
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Numerical models of holograms are available but their evaluation is a very computationally intensive task. We present an acceleration algorithm for optical field synthesis suitable for the reduced occlusion method of hologram synthesis. The acceleration uses an approximation that is designed for a field programmable gate array (FPGA) and therefore it mostly uses fixed point numbers. The work describes the approximation, its fixed-point modification, and the resulting FPGA structure. The results presented show that the solution produces high-quality holograms in a significantly reduced time due to efficient FPGA implementation. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3205081]
Real-Time Digital Simulation (RTDS) is a powerful tool in modeling and analyzing electrical and drive systems because it provides an efficient and accurate process. There are several hardware devices for this type of ...
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Real-Time Digital Simulation (RTDS) is a powerful tool in modeling and analyzing electrical and drive systems because it provides an efficient and accurate process. There are several hardware devices for this type of simulation;however, their high costs have led to the increasing use of more affordable and reconfigurable technologies. In this context, many logic blocks and storage elements make the field programmable gate array (FPGA) an ideal device to perform RTDS. This work proposes a technique to embed a real-time digital simulator in an FPGA through Hardware Description Language (HDL) since it provides liberty in the architecture choice and no dependency on commercial ready-made hardware-software packages. The approach proposed focuses on system design developing with expression tree graph, synthesizing and verifying, prioritizing the performance and design accuracy concerning area and power consumption. Thus, the result acquisition occurs at a time step considered in real-time. A simulation of a direct current (DC) motor speed control has been incorporated into this work as an example of application, which includes the embedding and simulation of the electric machine and its drive system. Performance tests have shown that the developed simulator is real-time and makes possible realistic analysis of the interaction between the plant and its control. In addition, an idea of the hardware requirement for real-time simulation is proposed based on the number of mathematical operations.
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