Trustworthy AI for Process Automation on a Chylla-Haase Polymerization Reactor

by   Daniel Hein, et al.
Siemens AG

In this paper, genetic programming reinforcement learning (GPRL) is utilized to generate human-interpretable control policies for a Chylla-Haase polymerization reactor. Such continuously stirred tank reactors (CSTRs) with jacket cooling are widely used in the chemical industry, in the production of fine chemicals, pigments, polymers, and medical products. Despite appearing rather simple, controlling CSTRs in real-world applications is quite a challenging problem to tackle. GPRL utilizes already existing data from the reactor and generates fully automatically a set of optimized simplistic control strategies, so-called policies, the domain expert can choose from. Note that these policies are white-box models of low complexity, which makes them easy to validate and implement in the target control system, e.g., SIMATIC PCS 7. However, despite its low complexity the automatically-generated policy yields a high performance in terms of reactor temperature control deviation, which we empirically evaluate on the original reactor template.


Interpretable Control by Reinforcement Learning

In this paper, three recently introduced reinforcement learning (RL) met...

Interpretable Policies for Reinforcement Learning by Genetic Programming

The search for interpretable reinforcement learning policies is of high ...

Computing Complexity-aware Plans Using Kolmogorov Complexity

In this paper, we introduce complexity-aware planning for finite-horizon...

Generating Interpretable Fuzzy Controllers using Particle Swarm Optimization and Genetic Programming

Autonomously training interpretable control strategies, called policies,...

Co-Training an Observer and an Evading Target

Reinforcement learning (RL) is already widely applied to applications su...

Cascade Attribute Network: Decomposing Reinforcement Learning Control Policies using Hierarchical Neural Networks

Reinforcement learning methods have been developed to achieve great succ...

Optimal Network Control in Partially-Controllable Networks

The effectiveness of many optimal network control algorithms (e.g., Back...

Please sign up or login with your details

Forgot password? Click here to reset