OS-aware automotive controller design using non-uniform sampling

Automotive functionalities typically consist of a large set of periodic/cyclic tasks scheduled under a real-time operating system (OS). Many of the tasks are feedback control applications with stringent performance requirements. OSEK/VDX is a common class of automotive OS that offers preemptive periodic schedules supporting a pre-configured set of periods. The feedback controllers implemented onto such OSEK/VDX-compliant systems need to use one of the pre-configured (sampling) periods. A shorter period is often desired for a higher control performance, and this implies a higher processor load. For a given performance requirement, the longest sampling period that meets this requirement is the optimal one. Given a limited set of pre-configured periods, such optimal sampling periods are often not available, and the practice is to choose a shorter available period—leading to a higher processor load. To address this, we propose a controller that cyclically switches among the available periods, thereby leading to an average sampling period closer to the optimal one. This way, we reduce the processor load and are able to pack more control applications on the same processor. The main challenge in this article is the design of such controllers that takes into account such cyclic switching of sampling periods (i.e., use non-uniform sampling). The controller needs to meet specified performance requirements (settling time) and system constraints (e.g., input saturation). Such a non-convex constrained controller optimization problem as raised in the OS-aware automotive systems design has not been addressed in the traditional optimal control literature. A novel approach based on adaptively parameterized particle swarm optimization (PSO) is proposed to solve it. Using the OS-aware controller design with non-uniform sampling, we show that a higher number of applications can be packed on a processor, which is of particular interest in the cost-sensitive automotive industry.