A neuromorphic control architecture inspired by the limbic system
| Autor: | Scola, Ignacio Rubio, Rodolfo Garcia Carrillo, Luis, Stewart, Terrence C., Sornborger, Andrew T. |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | 2021 60th IEEE Conference on Decision and Control (CDC). |
| DOI: | 10.1109/cdc45484.2021.9683790 |
| Popis: | We introduce a performance-guaranteed Limbic System-Inspired Control (LISIC) which is appropriate for implementation in neuromorphic hardware. The control strategy aims to stabilize the tracking error of a class of nonlinear systems with uncertain dynamics and external perturbations. The objective of the LISIC structure is to identify and compensate model differences between the theoretical assumptions considered and the actual conditions encountered in the real-time system to be controlled, using a minimum of energy in the computation. To validate our approach, we make use of a neuromorphic architecture composed by spiking neuronal networks, and using Nengo Brain Maker software we emulate a hardware implementation of our controller in Intel’s neuromorphic research processor codenamed Loihi. Numerical results are provided to demonstrate the tracking of the perturbed inverted pendulum with the neuromorphic control system. 2021 60th IEEE Conference on Decision and Control (CDC), December 14-17, 2021, Austin, TX, USA |
| Databáze: | OpenAIRE |
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