Parametrized Maximal Admissible Sets With Application to Constraint Management of Systems With Slowly Varying Parameters

Abstract Real-time constraint management schemes for time-varying or parameter-varying systems often result in conservative (slow) responses or carry a heavy computational burden. This makes some of the existing solutions less suitable for practical applications within these systems. To address this issue, this paper proposes a numerically efficient reference governor (RG) scheme for constraint management of systems with slowly time-varying parameters and constraints. The solution, which we call the adaptive-contractive reference governor (RG-AC), utilizes a contractive, parameterized characterization of the so-called maximal admissible set (MAS). To ensure low computational overhead, this parameter-dependent MAS (PD-MAS) is approximated using a sensitivity-based method that describes the changes in the facets of PD-MAS as a function of the system parameters around a nominal operating point. The computational and theoretical properties of the PD-MAS and RG-AC are presented. The effectiveness and limitations of the proposed method are demonstrated by studying a basic mass–spring–damper system.

Authors

Institutions

Publication Details

Journal
Journal of Dynamic Systems Measurement and Control
Published
2024-12-21
DOI
https://doi.org/10.1115/1.4067513
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Parametrized Maximal Admissible Sets With Application to Constraint Management of Systems With Slowly Varying Parameters

Collin Freiheit, Dhananjay Anand, Hamid R. Ossareh, Yasaman Pedari
Journal of Dynamic Systems Measurement and Control
Scheduling and Optimization Algorithms
article

Parametrized Maximal Admissible Sets With Application to Constraint Management of Systems With Slowly Varying Parameters

Collin Freiheit, Dhananjay Anand, Hamid R. Ossareh, Yasaman Pedari
article en

Abstract

Abstract Real-time constraint management schemes for time-varying or parameter-varying systems often result in conservative (slow) responses or carry a heavy computational burden. This makes some of the existing solutions less suitable for practical applications within these systems. To address this issue, this paper proposes a numerically efficient reference governor (RG) scheme for constraint management of systems with slowly time-varying parameters and constraints. The solution, which we call the adaptive-contractive reference governor (RG-AC), utilizes a contractive, parameterized characterization of the so-called maximal admissible set (MAS). To ensure low computational overhead, this parameter-dependent MAS (PD-MAS) is approximated using a sensitivity-based method that describes the changes in the facets of PD-MAS as a function of the system parameters around a nominal operating point. The computational and theoretical properties of the PD-MAS and RG-AC are presented. The effectiveness and limitations of the proposed method are demonstrated by studying a basic mass–spring–damper system.

Journal of Dynamic Systems Measurement and ControlVol. 147(4)
University of Vermont (US), National Institute of Standards and Technology (US), National Institute of Standards (EG), AM Technologies (Poland) (PL)
Openalex Percentile: Top 65%
Scheduling and Optimization Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Parametrized Maximal Admissible Sets With Application to Constraint Management of Systems With Slowly Varying Parameters — Collin Freiheit, Dhananjay Anand, et al. · Journal of Dynamic Systems Measurement and Control (2024) | TGRS Research Map | TGRS