Experimental evaluation of slack management in real-time control systems: Coordinated vs. self-triggered approach

Effective slack management, i.e., management of unused computing resources, for real-time control tasks mandates to redistribute the available resources between controllers as a function of the state of the controlled plants. Slack can be allocated to control tasks to alter their rate of progress via e.g., the controllers’ period, in order to adapt their behavior to changes in the computing platform and in the environment. This paper presents an experimental evaluation of two representative slack redistribution policies for multitasking real-time control systems: “coordinated” vs. “self-triggered”. In the coordinated policy a resource manager is responsible for modifying each control task progress. Alternatively, in the self-triggered policy, each control task decides its progress. The demands that each policy poses to the computing platform are analyzed and different operating system architectures providing flexibility and adaptivity are discussed. A proof-of-concept implementation including the real-time control of three double integrator plants in the form of electronic circuits is presented, and a complete performance analysis is reported.