Self-repairing Control against Actuator Failures Using a Spiking Neuron Model
- https://doi.org/10.2991/jrnal.k.200909.004How to use a DOI?
- Self-repairing control, actuator failure, fault detection, dynamic redundancy, spiking neuron model
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.
- © 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/).
Cite this article
TY - JOUR AU - Masanori Takahashi PY - 2020 DA - 2020/09 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 - https://doi.org/10.2991/jrnal.k.200909.004 ID - Takahashi2020 ER -