摘要
针对信息物理系统环境下可能发生的信息丢包问题,提出一种随机分布式预测控制的分析与设计方法.考虑控制器端到执行器端的传输丢包,采用马尔科夫过程对这一丢包过程进行描述.通过对马尔科夫跳变的线性模型进行增广,研究一种具有随机丢包不确定系统的分布式预测控制方法;将系统分解成多个子系统进行描述,研究基于最小最大化优化的分布式预测控制器设计方法,并提出基于迭代交互的子控制器协调算法.将随机分布式预测控制算法在实际电机系统中进行仿真测试,以验证所提出方法的有效性.
Aiming at the packet loss problem that may occur under the structure of Cyber-Physical Systems,an analysis and design method of stochastic distributed model predictive control is proposed.The packet dropouts from the controller to actuator transmission channel is modeled with the Markov process.By augmenting the linear model of Markov jump,a distributed model predictive control method is designed for the stochastic uncertain system with packet loss.The system is decomposed into multiple subsystems,a stochastic distributed predictive control is designed based on the minimum maximization optimization problem.An iterative algorithm is proposed for the coordination of the distributed predictive controllers.The proposed distributed predictive control algorithm is tested on a DC motor system,and is verified to be e?ective.
作者
杨晓峰
谢巍
张浪文
YANG Xiao-feng;XIE Wei;ZHANG Lang-wen(College of Automation Science and Technology,South China University of Technology,Guangzhou 510640,China)
出处
《控制与决策》
EI
CSCD
北大核心
2020年第8期1895-1901,共7页
Control and Decision
基金
国家自然科学基金项目(61803161)
广东省引进创新创业团队计划项目(2016YT03G125)
江门市创新科研团队引进项目(2017TD03)
广东省科技计划项目(2018B010108001,2017B090914001,2017A040405023,2017B090901040,2017B030306017)
广州市科技计划项目(201707010152)
广东省自然科学基金项目(2018A030310371)
中央高校基本科研业务费专项资金项目(2018A030310371)。
