Robust Control Barrier Functions for Safety Using a Hybrid Neuroprosthesis

被引:1
|
作者
Lambeth, Krysten [1 ]
Singh, Mayank [2 ]
Sharma, Nitin [1 ]
机构
[1] NC State Univ, UNC NC State Joint Dept Biomed Engn, Raleigh, NC 27606 USA
[2] NC State Univ, NC State Dept Elect & Comp Engn, Raleigh, NC 27606 USA
关键词
ELECTRICAL-STIMULATION; FES; WALKING;
D O I
10.23919/ACC55779.2023.10155862
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many lower-limb hybrid neuroprostheses lack powered ankle assistance and thus cannot compensate for functional electrical stimulation-induced muscle fatigue at the ankle joint. The lack of a powered ankle joint poses a safety issue for users with foot drop who cannot volitionally clear the ground during walking. We propose zeroing control barrier functions (ZCBFs) that guarantee safe foot clearance and fatigue mitigation, provided that the trajectory begins within the prescribed safety region. We employ a backstepping-based model predictive controller (MPC) to account for activation dynamics, and we formulate a constraint to ensure the ZCBF is robust to modeling uncertainty and disturbance. Simulations show the superior performance of the proposed robust MPC-ZCBF scheme for achieving foot clearance compared to traditional ZCBFs and Euclidean safety constraints.
引用
收藏
页码:54 / 59
页数:6
相关论文
共 50 条
  • [1] Adaptive Safety Using Control Barrier Functions and Hybrid Adaptation
    Maghenem, Mohamed
    Taylor, Andrew J.
    Ames, Aaron D.
    Sanfelice, Ricardo G.
    [J]. 2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 2418 - 2423
  • [2] Robust Exponential Control Barrier Functions for Safety-Critical Control
    Chinelato, Caio I. G.
    Angelico, Bruno A.
    [J]. 2021 AMERICAN CONTROL CONFERENCE (ACC), 2021, : 2342 - 2347
  • [3] Robust control barrier–value functions for safety-critical control
    Choi, Jason J.
    Lee, Donggun
    Sreenath, Koushil
    Tomlin, Claire J.
    Herbert, Sylvia L.
    [J]. arXiv, 2021,
  • [4] Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
    Robey, Alexander
    Lindemann, Lars
    Tu, Stephen
    Matni, Nikolai
    [J]. IFAC PAPERSONLINE, 2021, 54 (05): : 1 - 6
  • [5] Disturbance Observers for Robust Safety-Critical Control With Control Barrier Functions
    Alan, Anil
    Molnar, Tamas G.
    Das, Ersin
    Ames, Aaron D.
    Orosz, Gabor
    [J]. IEEE CONTROL SYSTEMS LETTERS, 2023, 7 : 1123 - 1128
  • [6] Robust Control Barrier-Value Functions for Safety-Critical Control
    Choi, Jason J.
    Lee, Donggun
    Sreenath, Koushil
    Tomlin, Claire J.
    Herbert, Sylvia L.
    [J]. 2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2021, : 6814 - 6821
  • [7] Robust Perimeter Defense using Control Barrier Functions
    Guerrero-Bonilla, Luis
    Nieto-Granda, Carlos
    Egerstedt, Magnus
    [J]. 2021 INTERNATIONAL SYMPOSIUM ON MULTI-ROBOT AND MULTI-AGENT SYSTEMS (MRS), 2021, : 164 - 172
  • [8] Maneuvering with safety guarantees using control barrier functions
    Marley, Mathias
    Skjetne, Roger
    Basso, Erlend
    Teel, Andrew R.
    [J]. IFAC PAPERSONLINE, 2021, 54 (16): : 370 - 377
  • [9] Poster on Safety Characterization in Hybrid Inclusions Using Barrier Functions
    Mghenem, Mohamed
    Sanfelice, Ricardo G.
    [J]. PROCEEDINGS OF THE 2019 22ND ACM INTERNATIONAL CONFERENCE ON HYBRID SYSTEMS: COMPUTATION AND CONTROL (HSCC '19), 2019, : 282 - 283
  • [10] Safe control synthesis using environmentally robust control barrier functions
    Hamdipoor, Vahid
    Meskin, Nader
    Cassandras, Christos G.
    [J]. EUROPEAN JOURNAL OF CONTROL, 2023, 74