Design process and tools for dynamic neuromechanical models and robot controllers. .. FEEDBACKDESIGN automates the analysis presented in Sects. 3.1 and 3.2. The user provides parameter values for a closed- or open-loop network of neurons, synapses, and a servomotor and limb if desired. Neurons that interface as inputs or outputs to the servomotor, and that feedback to the input neuron, are specified by the user. The equilibrium state is found by simulating the system until the energy goes to 0. If this happens, then the eigenvalues of the equilibrium point are found to ensure that the point is stable. If instead the energy diverges, the system is deemed unstable and no further analysis is conducted. The transfer function is generated for each neuron and neuron-servomotor complex, and the open-loop transfer function of each node (i.e. neuron or servomotor) is calculated by compounding Eqs. 34 and 35 for each node along the path. The closed loop transfer function is calculated by Eq. 39. The user can also query the stability margins, which are calculated by using a Newton minimizer to find the crossing points of the gain and phase responses (Sect. 3.2). The system’s parameter values can be varied and these analyses repeated to produce plots like those in Figs. 3 and 4. FEEDBACKDESIGN can be downloaded at +http://biorobots.case.edu/download/neural_des+ +ign_tools/FEEDBACKDESIGN.zip+.
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References in zbMATH (referenced in 2 articles )
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- Naris, Mantas; Szczecinski, Nicholas S.; Quinn, Roger D.: A neuromechanical model exploring the role of the common inhibitor motor neuron in insect locomotion (2020)
- Szczecinski, Nicholas S.; Hunt, Alexander J.; Quinn, Roger D.: Design process and tools for dynamic neuromechanical models and robot controllers (2017)