An Embedded Input-constrained MPC Solver for Network of Robots

Haishan ZHANG; Fengrong XU; Ka Ming LAM; Bo LAN; Guangzhi TIAN; Ling SHI

doi:10.1016/j.ifacol.2025.07.060

An Embedded Input-constrained MPC Solver for Network of Robots

Haishan ZHANG
, Fengrong XU
, Ka Ming LAM
, Bo LAN
, Guangzhi TIAN
, Ling SHI

Department of Electronic and Computer Engineering

Research output: Contribution to journal › Conference article published in journal › peer-review

Abstract

In this paper, we propose a lightweight online embedded solver for input-constrained model predictive control problems on low-power, resource-constrained microcontrollers. Our method combines gradient projection and conjugate gradient techniques to quickly identify the optimal working set within an active-set strategy. Both simulations and real-world tests confirm that the proposed solver yields optimized inputs with reduced overshoot and enhanced smoothness, demonstrating its effectiveness on resource-limited hardware.

Original language	English
Pages (from-to)	151-156
Number of pages	6
Journal	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	59
Issue number	4
DOIs	https://doi.org/10.1016/j.ifacol.2025.07.060
Publication status	E-pub ahead of print - 29 Jul 2025
Event	10th IFAC Conference on Networked Systems, NECSYS 2025 - Hong Kong, Hong Kong Duration: 2 Jun 2025 → 5 Jun 2025

Bibliographical note

Publisher Copyright:
© 2025 Elsevier B.V.. All rights reserved.

Keywords

Embedded computer control systems and applications
Model predictive control
Real time optimization and control

Access to Document

10.1016/j.ifacol.2025.07.060Licence: CC BY-NC-ND

Cite this

@article{d754d52c5e9a42c9acb0b2852ca14bd1,

title = "An Embedded Input-constrained MPC Solver for Network of Robots",

abstract = "In this paper, we propose a lightweight online embedded solver for input-constrained model predictive control problems on low-power, resource-constrained microcontrollers. Our method combines gradient projection and conjugate gradient techniques to quickly identify the optimal working set within an active-set strategy. Both simulations and real-world tests confirm that the proposed solver yields optimized inputs with reduced overshoot and enhanced smoothness, demonstrating its effectiveness on resource-limited hardware.",

keywords = "Embedded computer control systems and applications, Model predictive control, Real time optimization and control",

author = "Haishan ZHANG and Fengrong XU and LAM, \{Ka Ming\} and Bo LAN and Guangzhi TIAN and Ling SHI",

year = "2025",

month = jul,

day = "29",

doi = "10.1016/j.ifacol.2025.07.060",

language = "English",

volume = "59",

pages = "151--156",

journal = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

issn = "1474-6670",

publisher = "Elsevier B.V.",

number = "4",

}

TY - JOUR

T1 - An Embedded Input-constrained MPC Solver for Network of Robots

AU - ZHANG, Haishan

AU - XU, Fengrong

AU - LAM, Ka Ming

AU - LAN, Bo

AU - TIAN, Guangzhi

AU - SHI, Ling

PY - 2025/7/29

Y1 - 2025/7/29

N2 - In this paper, we propose a lightweight online embedded solver for input-constrained model predictive control problems on low-power, resource-constrained microcontrollers. Our method combines gradient projection and conjugate gradient techniques to quickly identify the optimal working set within an active-set strategy. Both simulations and real-world tests confirm that the proposed solver yields optimized inputs with reduced overshoot and enhanced smoothness, demonstrating its effectiveness on resource-limited hardware.

AB - In this paper, we propose a lightweight online embedded solver for input-constrained model predictive control problems on low-power, resource-constrained microcontrollers. Our method combines gradient projection and conjugate gradient techniques to quickly identify the optimal working set within an active-set strategy. Both simulations and real-world tests confirm that the proposed solver yields optimized inputs with reduced overshoot and enhanced smoothness, demonstrating its effectiveness on resource-limited hardware.

KW - Embedded computer control systems and applications

KW - Model predictive control

KW - Real time optimization and control

UR - https://www.scopus.com/pages/publications/105012473555

UR - https://openalex.org/works/w4413097633

U2 - 10.1016/j.ifacol.2025.07.060

DO - 10.1016/j.ifacol.2025.07.060

M3 - Conference article published in journal

SN - 1474-6670

VL - 59

SP - 151

EP - 156

JO - IFAC Proceedings Volumes (IFAC-PapersOnline)

JF - IFAC Proceedings Volumes (IFAC-PapersOnline)

IS - 4

T2 - 10th IFAC Conference on Networked Systems, NECSYS 2025

Y2 - 2 June 2025 through 5 June 2025

ER -

An Embedded Input-constrained MPC Solver for Network of Robots

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this