摘要
复杂大规模预测控制系统的在线实施一直是工业界十分关注的问题之一 ,本文针对工业环境下分布式网络结构的特点 ,提出了一种基于纳什最优的分布式预测控制优化算法 ,在以低成本在线实施的同时 ,保持了良好的控制性能 ,文中进一步给出了分布式线性模型预测控制算法的收敛条件 ,仿真结果表明了该算法的有效性 .
On-line optimization of predictive control strategy for the complex large-scale systems has been one of the focuses in industry. In this paper, a distributed model predictive control algorithm based on Nash optimality is proposed, which accords with the characteristics of distributed network under the industrial environment and can greatly improve the control performance with low cost. The convergence condition for distributed linear model predictive control algorithm is also given, and the simulation results demonstrate its effectiveness.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2002年第5期793-796,共4页
Control Theory & Applications
基金
国家自然科学基金重点项目 ( 6 99340 2 0 )
国家 973计划(G19980 30 415 )资助项目