SESYJul 17, 2012

On Model Based Synthesis of Embedded Control Software

arXiv:1207.4474v215 citations
AI Analysis

This addresses resource constraints in embedded systems by enabling smaller control software, though it is incremental as it builds on existing formal model-based synthesis methods.

The paper tackles the problem of automatically generating control software for embedded systems from formal models, where existing methods produce code that grows exponentially with bit precision, and shows that by trading off system-level performance for software size, the new controller can be less than 6% the size of the time-optimal one for a 12-bit inverted pendulum benchmark.

Many Embedded Systems are indeed Software Based Control Systems (SBCSs), that is control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for control software. Given the formal model of a plant as a Discrete Time Linear Hybrid System and the implementation specifications (that is, number of bits in the Analog-to-Digital (AD) conversion) correct-by-construction control software can be automatically generated from System Level Formal Specifications of the closed loop system (that is, safety and liveness requirements), by computing a suitable finite abstraction of the plant. With respect to given implementation specifications, the automatically generated code implements a time optimal control strategy (in terms of set-up time), has a Worst Case Execution Time linear in the number of AD bits $b$, but unfortunately, its size grows exponentially with respect to $b$. In many embedded systems, there are severe restrictions on the computational resources (such as memory or computational power) available to microcontroller devices. This paper addresses model based synthesis of control software by trading system level non-functional requirements (such us optimal set-up time, ripple) with software non-functional requirements (its footprint). Our experimental results show the effectiveness of our approach: for the inverted pendulum benchmark, by using a quantization schema with 12 bits, the size of the small controller is less than 6% of the size of the time optimal one.

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