未来航空动力呈现宽域多模式变循环调节、跨域多目标控制需求等特征，牵引下一代控制系统向分布式、多电混电、智能化、主动安全方向跃迁。针对当前分布式系统控制与诊断任务协同设计缺失、高度依赖物理冗余与保守裕度实现安全性、传统算法面临性能瓶颈等问题，本文依托双变循环发动机原理样机提出了多电分布式控制系统方案，及一种主动安全架构下的分布式控制诊断一体化综合设计方法，旨在实现主动容错直接性能量控制与分层分级诊断的有机协同。基于机载性能与余度观测单元实现性能量估计、稳定裕度估计与控制系统解析余度，并基于智能学习实现全生命周期基线模型管理与机载自适应模型修正，提出了多尺度信息融合的直接性能量主动稳定控制算法，并融合分层分级诊断策略实现智能回路切换、解析余度切换等，保证系统安全的同时充分释放性能潜力。最后，通过分布式硬件在环（DHIL）平台验证了本文方法的有效性。
Future aviation power exhibits characteristics such as wide-range multi-mode variable cycle regulation and cross-domain multi-objective control requirements, driving the next-generation control systems towards distributed, more-electric, hybrid-electric, intelligent, and proactive safety directions. Addressing the current issues of deficiency in collaboration between control and diagnostic tasks in distributed systems, high dependence on physical redundancy and conservative margins for safety, and performance bottlenecks with traditional algorithms, this paper proposes a more-electric distributed control system solution based on a dual-variable cycle engine prototype, along with an integrated approach to distributed control and diagnostics under an active safety architecture. The aim is to achieve organic synergy between proactive fault-tolerant direct performance control and hierarchical diagnostic strategies. Based on on-board performance and redundancy observation units, it enables performance estimation, stability margin estimation, and analytical redundancy of the control system, and through intelligent learning, it manages baseline models throughout the lifespan and on-board adaptive model corrections. The paper introduces a multi-scale information fusion-based direct performance active stabilization control algorithm, integrating hierarchical diagnostic strategies to achieve intelligent loop switching and analytical redundancy switching, ensuring system safety while fully unleashing performance potential. Finally, the effectiveness of the proposed method is validated through a distributed hardware-in-the-loop (DHIL) platform.
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