Repetitive model predictive control using linear matrix inequalities

Pradeep Y. Tiwari, Mayuresh V. Kothare

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Repetitive systems can be characterized by two time variables, namely, the finite time within each repeating cycle and the cycle index, each embodying a distinct connotation of time. Conventional optimal control theory does not explicitly account for this two dimensional (2D) description of repetitive systems. We propose a new formulation for control of repetitive systems using Model Predictive Control (MPC) that explicitly incorporates a 2D representation of the system. The proposed formulation uses a 2D Lyapunov function and the stability requirements are established along each time dimension of the system. The resulting controller synthesis problem is expressed in convex form using Linear Matrix Inequalities (LMIs). The approach allows explicit incorporation of input/output constraints in the controller design. Two examples illustrate the applicability of the proposed approach.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
Number of pages6
StatePublished - 2008
Externally publishedYes
Event2008 American Control Conference, ACC - Seattle, WA, United States
Duration: Jun 11 2008Jun 13 2008


Other2008 American Control Conference, ACC
Country/TerritoryUnited States
CitySeattle, WA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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