Data driven- Adaptive single neuron predictive controller based on Lyapunov approach
In this paper, a novel data driven-adaptive single neuron predictive controller is proposed. The self-tuning algorithm for the single neuron predictive controller is derived by a rigorous analysis based on the Lyapunov method such that the predicted tracking error convergences asymptotically. Simulation results are presented to illustrate the proposed adaptive predictive controller and a comparison with its conventional counterparts is made.