Probabilistic Invariant Sets for Closed-Loop Re-Identification

被引:3
作者
Anderson, A. [1 ]
Ferramosca, A. [2 ]
Gonzalez, A. H. [1 ]
Kofman, E. [3 ,4 ]
机构
[1] UNL, CONICET, Inst Technol Dev Chem Ind INTEC, Guemes 3450, RA-3000 Santa Fe, Argentina
[2] UTN, CONICET, Fac Reg Reconquista, Calle 44,1000, RA-3560 Reconquista, Santa Fe, Argentina
[3] Univ Nacl Rosario, FCEIA, Dept Control, RA-2000 Rosario, Santa Fe, Argentina
[4] Consejo Nacl Invest Cient & Tecn, CIFASIS, RA-1033 Buenos Aires, DF, Argentina
关键词
Model predictive control; closed-loop identification; probabilistic invariant set; PREDICTIVE CONTROL; IDENTIFICATION;
D O I
10.1109/TLA.2016.7555248
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, a Model Predictive Control (MPC) suitable for closed-loop re-identification was proposed, which solves the potential conflict between the persistent excitation of the system and the stabilization of the closed-loop by extending the equilibrium-point-stability to the invariant-set-stability. The proposed objective set, however, derives in large regions that contain conservatively the excited system evolution. In this work, based on the concept of probabilistic invariant sets, the controller target sets are substantially reduced ensuring the invariance with a sufficiently large probability (instead of deterministically), giving the resulting MPC controller the necessary flexibility to be applied in a wide range of systems.
引用
收藏
页码:2744 / 2751
页数:8
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