In the past two decades, advances in programmable device technologies, in both the hardware and software arenas, have been extraordinary. The original application of rapid prototyping has been complemented with a large number of new applications that take advantage of the excellent characteristics of the latest devices. High speed, very large number of components, large number of supported protocols, and the addition of ready- to-use intellectual property cores make programmable devices the preferred choice of implementation and even deployment in mass production quantities. This paper surveys the advanced features, design tools, and application domains for field-programmable gate arrays (FPGAs). The main characteristics and structure of modern FPGAs are first described to show their versatility and abundance of available design resources. Software resources are also discussed, as they are the main enablers for the efficient exploitation of the design capabilities of these devices. Current application domains are described, such as configurable computing, dynamically reconfigurable systems, rapid system prototyping, communication processors and interfaces, and signal processing. This paper also presents the authors' prospective view of how FPGAs will evolve to enter new application domains in the future.

Field programmable gate arrays (FPGAs) have established themselves as one of the preferred digital implementation platforms in a plethora of current industrial applications, and extensions and improvements are still continuously being included in the devices. This paper reviews recent advancements in FPGA technology, emphasizing the novel features that may significantly contribute to the development of more efficient digital systems for industrial applications. Special attention is paid to the design paradigm shift caused by the availability of increasingly powerful embedded (and soft) processors, which transformed FPGAs from hardware accelerators to very powerful system-on-chip (SoC) platforms. New analog resources, floating-point operators, and hard memory controllers are also described, because of the great advantages they provide to designers. Software tools are being strongly influenced by the design paradigm shift, which requires from them a much better support for software developers. Focusing mainly on this issue, recent advancements in software resources [intellectual property (IP) cores and design tools] are also reviewed. The impact of new FPGA features in industrial applications is analyzed in detail in three main areas, namely digital real-time simulation, advanced control techniques, and electronic instrumentation, with focus on mechatronics, robotics, and power systems design. The way digital systems are being currently designed in these areas is comprehensively reviewed, and a critical analysis of how they could significantly benefit from new FPGA features is presented.

In this article a finite control set model predictive control, is used to track a current reference in a power converter connected to an $RL$ load. An artificial intelligence approach is presented for real-time determination of the weighting factor that regulates the average switching frequency, independently of the operating point. The article focuses on the design, training, and digital implementation of an artificial neural network (ANN) that can be developed in a low-cost control platform. It is presented a sampling and offline ANN training procedure, together with a low-cost hardware implementation based on integer quantization of the ANN. The abovementioned approach provides a standalone application, serving as a framework for the development of ANN applications for power-converters. The main advantage of the presented approach is that the ANN inference is executed in real time. In this way, the weighting factor is automatically updated in real-time, allowing the system to quickly adapt to any reference step changes, and consequently provide the desired behavior. Executing the setup in laboratory prototype confirmed the theoretical analysis and successful tracking of the reference frequency.

The Internet of Things (IoT) paradigm has quickly gone past various technological domains to become part of everyday life across the globe. Ubiquitous devices (things) with a certain amount of intelligence, capable of connecting to the Internet and sharing information collaboratively are now a widespread reality. The general perception today indicates that the IoT may become a technological milestone, with an impact similar to that caused by the advent of the Internet itself. It will transform the Internet from a human-centric platform, where most applications are focused on human-to-human interaction and where most of the data are provided by humans, to a machine-intensive platform.

In current CMOS nanometer technologies, aging effects may appear after relatively short operating times, compared to the expected lifetime of circuits. Therefore, there is an increasing need for on-chip aging monitoring, especially in high-performance, safety critical systems. This paper presents a programmable aging sensor that can be embedded in field-programmable gate array (FPGA)-based designs, using standard resources available in those devices and with minimal impact on the standard FPGA design flow. Given the limited amount of resources required by the sensor, it can be instantiated not only in the critical paths of a circuit, but also in those that may be identified to be more likely affected by aging effects. Experimental results, obtained in circuits of increasing complexity (where several sensors need to be used), are presented and discussed, demonstrating the good performance of the proposed sensor, as well as its low cost in terms of area overhead and power consumption. Results of aging experiments based on the standard US MIL-STD-883 Method 1015.50 “Burn-In Test” are also reported, demonstrating that the effect of aging on the sensor is negligible compared to that on the circuit under test, which is a key point for practical applicability. The proposed approach provides a novel and efficient solution to the specific FPGA design problems in this context, which are different from those addressed in application-specific integrated circuit design.

Decreasing profit margins and increasing concerns about animal welfare are boosting the interest for the development of monitoring and analysis technologies specifically targeting the poultry meat production process. In this context, this paper addresses monitoring of poultry activity in breeding farms. Specifically, it analyzes the suitability of different vision systems and image processing algorithms with this purpose. These systems and algorithms have been tested in an actual farm during a breeding cycle. Experimental results are presented demonstrating that density-based computations provide the best results, and that they can be carried out using either video or thermographic images, but the latter are a better option because of practical operating reasons related to varying, low light intensity conditions.