Enhancing functionality of complex plant hybrid control system using case-based reasoning

A hybrid control system with Case Based Reasoning (CBR) procedure is considered. It is intended for complex industrial plants in abnormal and fault situations where the conventional control systems cannot work autonomously. CBR systems allow capture and use a specific experience by Case Base (CB) creation, similarity assessment, case adaptation and learning new cases. Some new results are incorporated into the traditional CBR cycle, relevant to control tasks - uncertainty, presence of multivariant solutions from different operators, rational distribution of knowledge among autonomous agents, ontologies and CBR-system. Simulation results are represented for an industrial plant with a non-square matrix.