Adaptive Feedforward Neural Network Control with an Optimized Hidden Node Distribution

1 code implementation • 23 May 2020 • Qiong Liu, Dongyu Li, Shuzhi Sam Ge, Zhong Ouyang

Composite adaptive radial basis function neural network (RBFNN) control with a lattice distribution of hidden nodes has three inherent demerits: 1) the approximation domain of adaptive RBFNNs is difficult to be determined a priori; 2) only a partial persistence of excitation (PE) condition can be guaranteed; and 3) in general, the required number of hidden nodes of RBFNNs is enormous.

Learning Theory