Paper Info
Title
A Discrete-Time Optimization-Based Sliding Mode Control Law For Linear Systems With Input And State Constraints
Abstract
This paper proposes a discrete-time sliding mode control (DSMC) strategy for linear (possibly multi-input) systems with additive bounded disturbances, which guarantees the satisfaction of input and state constraints. The control law is generated by solving a finite-horizon optimal control problem at each sampling instant, aimed at obtaining a control variable that is as close as possible to a reference DSMC law, but at the same time enforces constraint satisfaction for all admissible disturbance values. Contrary to previously-proposed control approaches merging DSMC and model predictive control, our proposal guarantees the satisfaction of all standard properties of DSMC, and in particular the finite-time convergence of the state into a boundary layer of the sliding manifold.
Year
DOI
Venue
2018
10.1109/CDC.2018.8619503
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
Field
DocType
ISSN
Convergence (routing),Constraint satisfaction,Mathematical optimization,Optimal control,Linear system,Computer science,Control theory,Model predictive control,Control variable,Discrete time and continuous time,Law,Sliding mode control
Conference
0743-1546
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Matteo Rubagotti110211.63
Gian Paolo Incremona2709.40
A. Ferrara3953126.03