模型预测控制作为一种约束优化控制策略，在工业控制领域取得了巨大的成功。然而, 传统校正预测控制针对大规模复杂系统难以满足系统多目标优化、鲁棒性、可靠性、计算复杂性以及通信带宽等要求。鲁棒协同预测控制能够协同多个局部控制器实现全局优化目标或Nash优化，克服实际系统中存在的不确定性和未知扰动实现系统全局鲁棒稳定。针对鲁棒协同预测控制系统建模、分布式状态估计、协调策略以及保证闭环稳定性的李雅普诺夫函数选取等关键问题展开研究。运用鲁棒协同预测控制, 实现多源发电过程间的协同优化, 在满足约束条件下，实现以减少机组疲劳和磨损为核心的经济目标; 针对风电介入下电力系统负荷频率控制问题，运用鲁棒协同预测控制,在满足发电机变化速率约束、浆距角约束以及大气参数变化情况下，协同优化多源发电过程实现以清洁能源优先出力、火电机组节能降耗为核心的经济和环保指标，从而实现风电介入下互联电力系统的稳定、经济运行。

Model predictive control (MPC) has been developed to be a constraint optimal control strategy, which has made great achievement in industrial processing control. However, the regulatory MPCs are ineffective in controlling large scale systems, due to the multiple objective optimization requirement, the inherent computational complexity, the robustness and reliability issues, as well as the communication bandwidth limitations. The robust coordinated MPC can realize cooperation among subsystems to achieve the global optimization or Nash optimization, and guarantee the global stability under the system uncertainties and disturbances. The research is devoted to the system modeling, the distributed state estimation, the coordinated optimal algorithms and the selecting Lyapunov function with guaranteed properties and stability. Regarding the multi-source power generation system, the robust coordinated MPC needs to solve a typical multi-object optimization problem, to realize the coordination among different kinds of generation units. This coordination can achieve economic objective that minimize the number of frequency control (LFC) requests and unit generation reversals, which gradually create fatigue in generating units. In the intermittent wind-power-incorporated interconnected power system, the robust coordinated MPC is utilized to coordinate the conventional plant and the wind power plant, to minimize the thermal power output and maximize the renewable power output. Meanwhile, it should satisfy the multi-constraints, e.g., generation rate constraints (GRCs), pitch angle and changing weather conditions. Consequently, it realizes the coordinated optimization and facilitates the economical and stable running of multi-source power system.