Research on Control Strategies for Partially Observable Discrete Event Systems Based on Normal State Tree Structure

In the process of modeling and solving large-scale complex systems, issues with complex state structures and low computational efficiency are often encountered. For partially observable discrete event systems, this paper proposes a method that utilizes state tree structures for modeling and analyzes global behavior through local projections. It demonstrates the existence of non-blocking, weakly controllable coreachable and observable (WCCO) subpredicates and their solving algorithms. In order to effectively represent these complex system states, the paper employs the use of Binary Decision Diagrams (BDD), which are capable of compactly and efficiently representing state tree structures. The feasibility of the proposed algorithm is verified through practical examples, showing that the algorithm exhibits higher fault tolerance and flexibility in handling complex systems, enabling the development of more forgiving control strategies. This not only enhances the stability and reliability of the system but also provides new solutions for supervisory control in practical engineering applications.