Self-repairing Control against Actuator Failures Using a Spiking Neuron Model

DOI

10.2991/jrnal.k.200909.004How to use a DOI?

Keywords

Self-repairing control; actuator failure; fault detection; dynamic redundancy; spiking neuron model

Abstract

This paper presents a new Self-repairing Control System (SRCS) for plants with actuator failures. The proposed SRCS uses the well-known Izhikevich spiking neuron model as a fault detector. When the actuator fails, the neuron model is excited and then spikes occur. Thus, counting up spikes makes it possible to find failures. Compared with the existing active fault-tolerant control systems, the SRCS has the following advantages: one can not only set a maximum detection time in advance, but also construct a simple control system whose structure is independent of the mathematical model of the plant. To confirm the effectiveness of the SRCS, this paper shows theoretical performance analysis and numerical simulation.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Masanori Takahashi
PY  - 2020
DA  - 2020/09/14
TI  - Self-repairing Control against Actuator Failures Using a Spiking Neuron Model
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 160
EP  - 164
VL  - 7
IS  - 3
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.200909.004
DO  - 10.2991/jrnal.k.200909.004
ID  - Takahashi2020
ER  -