2000 character limit reached
Neuromorphic Control of a Pendulum
Published 8 Apr 2024 in eess.SY and cs.SY | (2404.05339v3)
Abstract: We illustrate the potential of neuromorphic control on the simple mechanical model of a pendulum, with both event-based actuation and sensing. The controller and the pendulum are regarded as event-based systems that occasionally interact to coordinate their respective rhythms. Control occurs through a proper timing of the interacting events. We illustrate the mixed nature of the control design: the design of a rhythmic automaton, able to generate the right sequence of events, and the design of a feedback regulator, able to tune the timing of events.
- D. Lakatos, F. Petit, and A. Albu-Schäffer, “Nonlinear oscillations for cyclic movements in human and robotic arms,” IEEE Transactions on Robotics, vol. 30, no. 4, pp. 865–879, 2014.
- M. M. Williamson, “Robot arm control exploiting natural dynamics,” Ph.D. dissertation, Massachusetts Institute of Technology, 1999.
- G. Garofalo, C. Ott, and A. Albu-Schäffer, “Walking control of fully actuated robots based on the bipedal slip model,” in 2012 IEEE International Conference on Robotics and Automation. IEEE, 2012, pp. 1456–1463.
- A. J. Ijspeert, A. Crespi, D. Ryczko, and J.-M. Cabelguen, “From swimming to walking with a salamander robot driven by a spinal cord model,” science, vol. 315, no. 5817, pp. 1416–1420, 2007.
- S. P. DeWeerth, L. Nielsen, C. A. Mead, and K. J. Åström, “A simple neuron servo,” IEEE Transactions on Neural Networks, vol. 2, no. 2, pp. 248–251, 1991.
- K.-E. Åarzén, “A simple event-based pid controller,” IFAC Proceedings Volumes, vol. 32, no. 2, pp. 8687–8692, 1999.
- E. Aranda-Escolastico, M. Guinaldo, R. Heradio, J. Chacon, H. Vargas, J. Sánchez, and S. Dormido, “Event-based control: A bibliometric analysis of twenty years of research,” IEEE Access, vol. 8, pp. 47 188–47 208, 2020.
- R. Sepulchre, “Spiking control systems,” Proceedings of the IEEE, 2022.
- C. Fernandez Lorden, “Neuromorphic control of embodied central pattern generators,” Université de Liège, Liège, Belgique, 2023, (Unpublished master’s thesis), https://matheo.uliege.be/handle/2268.2/18256.
- L. Ribar and R. Sepulchre, “Neuromorphic control: Designing multiscale mixed-feedback systems,” IEEE Control Systems Magazine, vol. 41, no. 6, pp. 34–63, 2021.
- R. Schmetterling, T. B. Burghi, and R. Sepulchre, “Adaptive conductance control,” Annual Reviews in Control, 2022.
- T. B. Burghi and R. Sepulchre, “Adaptive observers for biophysical neuronal circuits,” IEEE Transactions on Automatic Control, 2023.
- A. J. Ijspeert, “Central pattern generators for locomotion control in animals and robots: a review,” Neural networks, vol. 21, no. 4, pp. 642–653, 2008.
- A. J. Ijspeert, A. Crespi, and J.-M. Cabelguen, “Simulation and robotics studies of salamander locomotion: applying neurobiological principles to the control of locomotion in robots,” Neuroinformatics, vol. 3, pp. 171–195, 2005.
- E. Angelidis, E. Buchholz, J. Arreguit, A. Rougé, T. Stewart, A. von Arnim, A. Knoll, and A. Ijspeert, “A spiking central pattern generator for the control of a simulated lamprey robot running on spinnaker and loihi neuromorphic boards,” Neuromorphic Computing and Engineering, vol. 1, no. 1, p. 014005, 2021.
- H. X. Ryu and A. D. Kuo, “An optimality principle for locomotor central pattern generators,” Scientific Reports, vol. 11, no. 1, p. 13140, 2021.
- M. A. Lewis, F. Tenore, and R. Etienne-Cummings, “Cpg design using inhibitory networks,” in Proceedings of the 2005 IEEE international conference on robotics and automation. IEEE, 2005, pp. 3682–3687.
- M. F. Simoni and S. P. DeWeerth, “Two-dimensional variation of bursting properties in a silicon-neuron half-center oscillator,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 14, no. 3, pp. 281–289, 2006.
- A. D. Kuo, “The relative roles of feedforward and feedback in the control of rhythmic movements,” Motor control, vol. 6, no. 2, pp. 129–145, 2002.
- S. H. Strogatz, “Nonlinear dynamics and chaos,” 1996.
- D. Bucher, G. Haspel, J. Golowasch, and F. Nadim, “Central pattern generators,” eLS, pp. 1–12, 2015.
- E. Marder, S. Kedia, and E. O. Morozova, “New insights from small rhythmic circuits,” Current opinion in neurobiology, vol. 76, p. 102610, 2022.
- L. Ribar and R. Sepulchre, “Neuromodulation of neuromorphic circuits,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, no. 8, pp. 3028–3040, 2019.
- L. Ribar, “Synthesis of neuromorphic circuits with neuromodulatory properties,” Ph.D. dissertation, University of Cambridge, 2020.
- P. Lakatos, J. Gross, and G. Thut, “A new unifying account of the roles of neuronal entrainment,” Current Biology, vol. 29, no. 18, pp. R890–R905, 2019.
- P. Wieland, G. S. Schmidt, R. Sepulchre, and F. Allgöwer, “Phase synchronization through entrainment by a consensus input,” in 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010, pp. 534–539.
- E. Sontag, “Contractive systems with inputs,” in Perspectives in Mathematical System Theory, Control, and Signal Processing: A Festschrift in Honor of Yutaka Yamamoto on the Occasion of his 60th Birthday, J. C. Willems, S. Hara, Y. Ohta, and H. Fujioka, Eds. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 217–228.
- G. Russo, M. Di Bernardo, and E. Sontag, “Global entrainment of transcriptional systems to periodic inputs,” PLoS Computational Biology, vol. 6, no. 4, p. e1000739, 04 2010.
- P. Sacre and R. Sepulchre, “Sensitivity analysis of oscillator models in the space of phase-response curves: Oscillators as open systems,” IEEE Control Systems Magazine, vol. 34, no. 2, pp. 50–74, 2014.
- D. Efimov, P. Sacré, and R. Sepulchre, “Controlling the phase of an oscillator: a phase response curve approach,” in Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference. IEEE, 2009, pp. 7692–7697.
- R. Schmetterling, T. B. Burghi, and R. Sepulchre, “Robust online estimation of biophysical neural circuits,” in 2023 62nd IEEE Conference on Decision and Control (CDC). IEEE, 2023, pp. 703–708.
- T. B. Burghi, T. O’Leary, and R. Sepulchre, “Distributed online estimation of biophysical neural networks,” in 2022 IEEE 61st Conference on Decision and Control (CDC). IEEE, 2022, pp. 628–634.
- E. Marder, T. O’Leary, and S. Shruti, “Neuromodulation of circuits with variable parameters: single neurons and small circuits reveal principles of state-dependent and robust neuromodulation,” Annual review of neuroscience, vol. 37, pp. 329–346, 2014.
- G. A. Pratt, M. M. Williamson, P. Dillworth, J. Pratt, and A. Wright, “Stiffness isn’t everything,” in Experimental Robotics IV: The 4th International Symposium, Stanford, California, June 30–July 2, 1995. Springer, 1997, pp. 253–262.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.