Computer-controlled systems: theory and design (2nd ed.)
Computer-controlled systems: theory and design (2nd ed.)
Real-Time Systems: Design Principles for Distributed Embedded Applications
Real-Time Systems: Design Principles for Distributed Embedded Applications
Linear Systems
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
What's Ahead for Embedded Software?
Computer
Generating embedded software from hierarchical hybrid models
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
On task schedulability in real-time control systems
RTSS '96 Proceedings of the 17th IEEE Real-Time Systems Symposium
Convex Optimization
Dispatch Sequences for Embedded Control Models
RTAS '05 Proceedings of the 11th IEEE Real Time on Embedded Technology and Applications Symposium
Quantifying the Gap between Embedded Control Models and Time-Triggered Implementations
RTSS '05 Proceedings of the 26th IEEE International Real-Time Systems Symposium
Time-triggered implementations of dynamic controllers
EMSOFT '06 Proceedings of the 6th ACM & IEEE International conference on Embedded software
Regular Specifications of Resource Requirements for Embedded Control Software
RTAS '08 Proceedings of the 2008 IEEE Real-Time and Embedded Technology and Applications Symposium
Synchronous Programming of Reactive Systems
Synchronous Programming of Reactive Systems
Survey Invariant representations of discrete-time periodic systems
Automatica (Journal of IFAC)
Resource constrained LQR control under fast sampling
Proceedings of the 14th international conference on Hybrid systems: computation and control
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Bridging the gap between model-based design and platform-based implementation is one of the critical challenges for embedded software systems. In the context of embedded control systems that interact with an environment, a variety of errors due to quantization, delays, and scheduling policies may generate executable code that does not faithfully implement the model-based design. In this article, we show that the performance gap between the model-level semantics of linear dynamic controllers, for example, the proportional-integral-derivative (PID) controllers and their implementation-level semantics, can be rigorously quantified if the controller implementation is executed on a predictable time-triggered architecture. Our technical approach uses lifting techniques for periodic time-varying linear systems in order to compute the exact error between the model semantics and the execution semantics. Explicitly computing the impact of the implementation on overall system performance allows us to compare and partially order different implementations with various scheduling or timing characteristics.