Design and implementation of an Autonomous Systems Training Environment framework for control algorithm evaluation in autonomous plant operation

Abstract

The shortage of trained plant operators who can control complex systems in the process and energy industry is leading to an increasing need for more autonomy of such plants. In future, such systems will be controlled by autonomous agents executing intelligent control algorithms. Due to the critical nature of such plants and processes, new control strategies should not be introduced untested. In order to test suitable algorithms, robust and comprehensive simulation environments are required. In this paper, a framework, called Autonomous Systems Training Environment, is proposed for the evaluation of control algorithms in autonomous plant operations. Furthermore, an exemplary use case for a process engineering system is implemented in Matlab/Simulink, taking into account different levels of control (e.g., regulatory control, operator control, safety control). Faults, which represent a major challenge in the autonomous control, are also considered.