A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software

TL;DR

This paper introduces a novel Map-Reduce parallel algorithm and MPI implementation for automatic control software synthesis, significantly reducing computation time for large systems like inverted pendulums and buck converters.

Contribution

It presents the first parallel approach for control software synthesis using Map-Reduce, enabling faster synthesis for complex hybrid systems.

Findings

PQKS achieves over 65% efficiency.

Synthesis time reduced from 25 days to 16 hours on 60 processors.

Effective on classical control problems like inverted pendulum.

Abstract

Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software. Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis. In this paper, we present a Map-Reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis. We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.