New Decomposition Method for Cyber-Physical Systems Based on Interpreted Petri Nets

Petri nets are widely used for the modeling and analysis of Cyber-Physical Systems(CPS),which typically involve multiple concurrent tasks.To simplify the implementation of CPS,these systems can be decomposed into several independent components.Existing CPS decomposition methods,such as algorithms based on integer linear algebra,suffer from high time complexity,while decomposition methods that rely on monitors incur significant communication overhead.To address these issues,this paper integrates the advantages of existing decomposition approaches and proposes a novel CPS decomposition method based on Interpreted Petri Nets(IPN).The proposed method incrementally decomposes the network using constraint conditions,generating independent State Machine Components(SMCs) to effectively reduce the model size.Additionally,a new signal synchronization mechanism is introduced to replace traditional monitor-based schemes,significantly reducing synchronization overhead.Experimental results demonstrate that the proposed method achieves a decomposition time complexity of O<i>(n²) </i>in most test cases,which is far superior to the exponential complexity O<i>(2ⁿ) </i>of traditional methods.Furthermore,the generated component set is more compact and efficient.