Co-design of a controller and its digital implementation: the MOBY-DIC2 toolbox for embedded model predictive control

Several software tools are available in the literature for the design and embedded implementation of linear model predictive control (MPC), both in its implicit and explicit (either exact or approximate) forms. Most of them generate C code for easy implementation on a microcontroller, and the others can convert the C code into hardware description language code for implementation on a field programmable gate array (FPGA). However, a unified tool allowing one to generate efficient embedded MPC for an FPGA, starting from the definition of the plant and its constraints, was still missing. The MOBY-DIC2 toolbox described in this brief bridges this gap. To illustrate its functionalities, the tool is exploited to embed the controller and observer for a real buck power converter in an FPGA. This implementation achieves a latency of about 30 µs with the implicit controller and 240 μs with the approximate explicit controller

Resource-aware control and dynamic scheduling in CPS

\u3cp\u3eRecent developments in computer and communication technologies are leading to an increasingly networked and wireless world. This raises new challenging questions in the context of control for cyberphysical systems (CPS), especially when the computation, communication, energy and actuation resources (for control) of the system are limited and/or shared by multiple control tasks. These limitations obstruct the use of classical design techniques for feedback control algorithms and call for new resource-aware control paradigms. These new resource-aware control systems typically have to take both discrete decisions (which task is allowed to use the resource) and continuous decisions (which continuous control input is generated for the task). In this talk two approaches are presented to address this hybrid co-design problem. Both approaches result in control algorithms that exploit real-time measurement information available on the state of the CPS and decide dynamically on the actions to take. This leads to the situation that individual control tasks are no longer executed in classical periodic time-triggered patterns, but in aperiodic patterns with varying inter-execution times. By abandoning the periodic scheduling of control tasks, the aim is to realise better trade-offs between the overall performance of the CPS and the required resource utilisation. The approaches are illustrated by various applications. interesting challenges for the future are discussed as well.\u3c/p\u3