Iwasaki Tetsuya
Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22904-4746, USA.
Automatica (Oxf). 2008 Dec 1;44(12):3061-3069. doi: 10.1016/j.automatica.2008.05.024.
The central pattern generator (CPG) is a nonlinear oscillator formed by a group of neurons, providing a fundamental control mechanism underlying rhythmic movements in animal locomotion. We consider a class of CPGs modeled by a set of interconnected identical neurons. Based on the idea of multivariable harmonic balance, we show how the oscillation profile is related to the connectivity matrix that specifies the architecture and strengths of the interconnections. Specifically, the frequency, amplitudes, and phases are essentially encoded in terms of a pair of eigenvalue and eigenvector. This basic principle is used to estimate the oscillation profile of a given CPG model. Moreover, a systematic method is proposed for designing a CPG-based nonlinear oscillator that achieves a prescribed oscillation profile.
中枢模式发生器(CPG)是由一组神经元构成的非线性振荡器,为动物运动中的节律性运动提供了一种基本控制机制。我们考虑一类由一组相互连接的相同神经元建模的CPG。基于多变量谐波平衡的思想,我们展示了振荡轮廓如何与指定互连结构和强度的连接矩阵相关。具体而言,频率、振幅和相位基本上是根据一对特征值和特征向量进行编码的。这一基本原理用于估计给定CPG模型的振荡轮廓。此外,还提出了一种系统方法,用于设计基于CPG的非线性振荡器,以实现规定的振荡轮廓。