National Instruments Aust & NZ announces the release of the CompactRIO performance controller, a new software-designed controller integrating the latest embedded technologies from Intel and Xilinx to deliver excellent performance and flexibility.
Fully supported by LabVIEW 2014 and NI Linux Real-Time, the new CompactRIO performance controller is recommended for advanced control applications in harsh, industrial environments and provides high-performance processing, custom timing and triggering, and data transfer from modular C Series I/O.
Jamie Smith, director of embedded systems at NI explains that the LabVIEW RIO architecture breaks the barriers of traditional embedded system design and provides the best off-the-shelf platform to solve any demanding control and monitoring task. NI’s platform-based approach gives small design teams the confidence to build innovative embedded systems without wasting development time and cost.
Using LabVIEW 2014 with NI Linux Real-Time support, engineers and scientists can continue developing their system in a single, familiar development environment while taking immediate advantage of increased CompactRIO hardware performance.
Shahram Mehraban, global head of energy and industrial segments at the Intel Internet of Things Group observes that the Intel and NI collaboration allows industrial customers to benefit from the latest processing technologies while meeting their rugged performance requirements. Intel worked closely with NI during the early phases of product development to rapidly bring the latest Intel Atom processor to this segment.
Key features of the CompactRIO performance controllers include Intel Atom dual core processor to close the loop faster, tackle more tasks with the same controller, and process data with more precision, accuracy and speed; Kintex-7 FPGA to process more channels and implement more complex filtering and control algorithms; NI Linux Real-Time to get access to an extensive community of applications and IP with a robust Linux-based real-time OS; embedded UI to implement a local HMI device and use the control system to handle HMI tasks, cutting component costs as well as development and integration time; and improved vision integration by adding USB3 or GigE Vision cameras using NI Linux Real-Time, integrating vision acquisition directly into an application, and using new Vision IP to turn the FPGA into a high-performance vision coprocessor.