Research Article
Task-Oriented Parameter Tuning Based on Priority Condition for Biologically Inspired Robot Application
Table 2
Each parameter selected by the proposed tuning algorithm.
| Neural Oscillators | 1 | 2 | 3 | Control gains | | Inhibitory weight () | 1.897 | 2.540 | 2.284 | Virtual spring stiffness coef. () | 1897.6 | Adaptation constant () | 3.339 | 3.092 | 3.229 | Virtual damping coef. () | 65.341 | Tonic input () | 1.116 | 1.658 | 1.175 | Propotional gain for 1st neural input () | 1.247 | Sensory gain () | 2.298 | 1.013 | 1.383 | Propotional gain for 2nd neural input () | 3.014 | Rising time constant () | 0.295 | 0.222 | 0.160 | Propotional gain for 3rd neural input () | 2.502 | Adatation time constant () | 0.590 | 0.444 | 0.320 | | |
|
|