The optimization of consensus decision-making for a multi-microwave source system based on composite leader-follower clustering for intelligent agent-based joint heating temperature field

To address the issues of uneven temperature distribution and the difficulty of temperature control in microwave heating, a composite leader cluster consensus decision optimization strategy for multiple microwave source agents is proposed. This strategy aims to optimize the temperature field distribution and improve heating control accuracy. First, a distributed control framework for joint heating was established. Second, within this structure, multiple leader systems within the composite leader system were used for decision-making. Consensus decisions between multiple leader decision points were made through a weight allocation algorithm, achieving a dynamic balance between temperature control and temperature field optimization. Then, on the basis of the composite leader decision information, the feeding power of the microwave source cluster was coordinated via a consensus algorithm, achieving dynamic coordination and complementarity between the leader cluster and the follower cluster. Finally, the simulation results revealed that after adopting this strategy, the temperature control error rate ranged from 0.25% to 1.43%. Compared with a single leader decision system, the composite leader decision system improved the uniformity in the horizontal and vertical sections by 1% to 37% and 3.5% to 26.5%, respectively. Compared with traditional microwave heating methods, the uniformity in the horizontal and vertical sections was improved by 25.3% to 61.2% and 24.2% to 66.6%, respectively. These results verify that the proposed consistency heating strategy under composite leader consensus decision-making is feasible and efficient, achieving precise temperature control and optimization of the temperature field.