A new approach for intelligent control is proposed for complex uncertain plants using synergism between multi-agent and ontology based frameworks. A multi stage procedure is developed for situation recognition, strategy selection and control algorithm parameterization following coordinated objective function. Fuzzy logic based extension of conventional ontology is implemented to meet uncertainties in the plant, its environment and sensor information. Ant colony optimization is applied to realize trade-off between requirements and control resources as well as for significant reduction of the communication rate among the intelligente agents. To react on unexpected changes in operational conditions certain adaptation functionality of the fuzzy ontology is foreseen. A multi-dimensional cascade system is considered and some simulation results are presented for variety of strategies implemented.