Output Feedback Robust MPC Based-on Direct Input-Output Model

摘要：

This paper proposes a synthesis approach to output feedback robust model predictive control (RMPC) for systems with both polytopic description and bounded noise. Unlike previous works, we do not utilize the state space model. Hence, there is no requirement for estimating the bounds on the true state. We directly utilize the input-output model. The feedback control law is based on the current output, past outputs and past inputs. By on-line implementation of the controller, the output and input of the closed-loop system will converge to a neighborhood of the equilibrium point. A numerical example is given to illustrate the effectiveness of the controller.

关键词： Model predictive control Output feedback Input-output model Uncertain systems

作者: Baocang Ding

作者单位: Ministry of Education Key Lab For Intelligent Networks and Network Security (MOE KLINNS Lab), Department of Automation, School of Electronic and Information Engineering, Xian Jiao Tong University, Xian 710049, P. R. China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 86-91

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）