Multiple neural network based DCAL controllers using orthonormal activation function neural networks

Direct adaptive control schemes are developed using orthonormal activation function based neural networks (OAFNNs) for trajectory tracking control of a class of nonlinear systems. Multiple OAFNNs are employed in these controllers for feedforward compensation of unknown system dynamics. Choice of multiple OAFNNs allows a reduction in overall network size reducing the computational requirements. The network weights are tuned online in real time. The overall stability of the system and the neural networks is guaranteed using Lyapunov analysis. The developed neural controllers are evaluated experimentally and the experimental results support the theoretical analysis