FPGAs in Industrial Control Applications

The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs

Extensible FlexRay communication controller for FPGA-based automotive systems

Modern vehicles incorporate an increasing number of distributed compute nodes, resulting in the need for faster and more reliable in-vehicle networks. Time-triggered protocols such as FlexRay have been gaining ground as the standard for high-speed reliable communications in the automotive industry, marking a shift away from the event-triggered medium access used in controller area networks (CANs). These new standards enable the higher levels of determinism and reliability demanded from next-generation safety-critical applications. Advanced applications can benefit from tight coupling of the embedded computing units with the communication interface, thereby providing functionality beyond the FlexRay standard. Such an approach is highly suited to implementation on reconfigurable architectures. This paper describes a field-programmable gate array (FPGA)-based communication controller (CC) that features configurable extensions to provide functionality that is unavailable with standard implementations or off-the-shelf devices. It is implemented and verified on a Xilinx Spartan 6 FPGA, integrated with both a logic-based hardware ECU and a fully fledged processor-based electronic control unit (ECU). Results show that the platform-centric implementation generates a highly efficient core in terms of power, performance, and resource utilization. We demonstrate that the flexible extensions help enable advanced applications that integrate features such as fault tolerance, timeliness, and security, with practical case studies. This tight integration between the controller, computational functions, and flexible extensions on the controller enables enhancements that open the door for exciting applications in future vehicles

Gain scheduling automatic landing system by modeling Ground Effect

Taking ground effect into account a longitudinal automatic landing system is designed. Such a system will be tested and implemented on board by using the Preceptor N3 Ultrapup aircraft which is used as technological demonstrator of new control navigation and guidance algorithms in the context of the “Research Project of National Interest” (PRIN 2008) by the Universities of Bologna, Palermo, Ferrara and the Second University of Naples. A general mathematical model of the studied aircraft has been built to obtain non–linear analytical equations for aerodynamic coefficients both Out of Ground Effect and In Ground Effect. To cope with the strong variations of aerodynamic coefficients In Ground Effect a modified gain scheduling approach has been employed for the synthesis of the controller by using six State Space Models. Stability and control matrices have been evaluated by linearization of the obtained aerodynamic coefficients. To achieve a simple structure of the control system, an original landing geometry has been chosen, therefore it has been imposed to control the same state variables during both the glide path and the flare