The performance of a closed-loop system is a function not only of the controller, but also of the physical system parameters and computer architecture. Careful codesign of all subsystems can have a dramatic impact on the performance and robustness of the overall cyber-physical system, especially when implementing computationally demanding optimisation-based control methods. In this presentation, Eric outlines how Imperial College London has been integrating MATLAB^® and Simulink^® as part of their design process for hardware-in-the-loop testing, where a predictive controller is implemented in real-time on an FPGA target. They have used Model-Based Design to reduce costs and design time, improve reliability of algorithms over open source tools, and achieve performance specifications that are one or more orders of magnitude beyond the state-of-the-art.