Emulation-based Neuromorphic Control for the Stabilization of LTI Systems
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866911266574958592 |
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| author | Petri, Elena Scheres, Koen J. A. Steur, Erik H., W. P. M. Heemels |
| author_facet | Petri, Elena Scheres, Koen J. A. Steur, Erik H., W. P. M. Heemels |
| contents | Brain-inspired neuromorphic technologies can offer important advantages over classical digital clock-based technologies in various domains, including systems and control engineering. Indeed, neuromorphic engineering could provide low-latency, low-energy and adaptive control systems in the form of spiking neural networks (SNNs) exploiting spike-based control and communication. However, systematic methods for designing and analyzing neuron-inspired spiking controllers are currently lacking. This paper presents a new systematic approach for stabilizing linear time-invariant (LTI) systems using SNN-based controllers, designed as a network of integrate-and-fire neurons, whose input is the measured output from the plant and generating spiking control signals. The new approach consists of a two-step emulation-based design procedure. In the first step, we establish conditions on the neuron parameters to ensure that the spiking signal generated by a pair of neurons emulates any continuous-time signal input to the neurons with arbitrary accuracy in terms of a special metric for spiky signals. In the second step, we propose a novel stability notion, called integral spiking-input-to-state stability (iSISS) building on this special metric. We prove that an asymptotically stable LTI system has this iSISS property. By combining these steps, a certifiable practical stability property of the closed-loop system can be established. Generalizations are discussed and the effectiveness of the approach is illustrated in a numerical case study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_11875 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Emulation-based Neuromorphic Control for the Stabilization of LTI Systems Petri, Elena Scheres, Koen J. A. Steur, Erik H., W. P. M. Heemels Systems and Control Brain-inspired neuromorphic technologies can offer important advantages over classical digital clock-based technologies in various domains, including systems and control engineering. Indeed, neuromorphic engineering could provide low-latency, low-energy and adaptive control systems in the form of spiking neural networks (SNNs) exploiting spike-based control and communication. However, systematic methods for designing and analyzing neuron-inspired spiking controllers are currently lacking. This paper presents a new systematic approach for stabilizing linear time-invariant (LTI) systems using SNN-based controllers, designed as a network of integrate-and-fire neurons, whose input is the measured output from the plant and generating spiking control signals. The new approach consists of a two-step emulation-based design procedure. In the first step, we establish conditions on the neuron parameters to ensure that the spiking signal generated by a pair of neurons emulates any continuous-time signal input to the neurons with arbitrary accuracy in terms of a special metric for spiky signals. In the second step, we propose a novel stability notion, called integral spiking-input-to-state stability (iSISS) building on this special metric. We prove that an asymptotically stable LTI system has this iSISS property. By combining these steps, a certifiable practical stability property of the closed-loop system can be established. Generalizations are discussed and the effectiveness of the approach is illustrated in a numerical case study. |
| title | Emulation-based Neuromorphic Control for the Stabilization of LTI Systems |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2511.11875 |