Enhanced Interpreted Petri Nets for Industrial Processes

Hybrid control systems are an exciting field of research. These contain two distinct types of system; one with continuous dynamics and the other with discrete dynamics, that interact with each other. Model-based fault detection methods were proposed to detect and isolate faults as may occur in such systems; however, these methods are computationally demanding. This paper enhances a diagnoser interpreted Petri net (IPN) model to locate and isolate faults in such systems. The enhanced IPN model has two notable features, one it is simpler and the other it is faster. The latter feature stemmed from the fact that the proposed model consists of a single place and the same number of transitions that the system model has. Unlike, the conventional IPN-based diagnoser, the enhanced IPN-based diagnoser deals with complex hybrid control systems with ease. Industrial processes are employed to test the enhanced IPN diagnoser.