Case Study: B&R Industrial Automation achieves 70% faster development and improved servo-drive accuracy and speed with MathWorks MATLAB & Simulink

B&R Industrial Automation Improves Servo Drive Performance with Virtual Sensor Algorithms Developed Using Model-Based Design

B&R Industrial Automation needed to improve positioning accuracy and speed for flexible links on its ACOPOS servo drives without adding costly sensors. A three‑engineer team had under six months to prove and implement a virtual‑sensor approach, so B&R turned to MathWorks’ Model‑Based Design using MATLAB and Simulink to rapidly analyze, visualize, and prototype solutions.

Using MathWorks tools (MATLAB, Simulink, System Identification Toolbox, and Control System Toolbox), B&R created virtual‑sensor algorithms, a state‑space controller with a Kalman filter, validated the design via simulation and C MEX verification, and delivered an ACOPOS blockset for customers. The MathWorks‑based implementation reduced development time by about 70%, cut settling time by ~30%, increased position accuracy by at least 50%, and let customers simulate machines before hardware was available.

B&R Industrial Automation

Engelbert Gruenbacher

Team Leader of the Firmware Group