Robust adaptive learning control using spiking-based self-organizing emotional neural network for a class of nonlinear systems with uncertainties

For second-order general nonlinear systems with uncertainties, a control scheme combining fractional-order fast terminal sliding mode control (FOFTSMC) and self-organizing emotional neural network (SOENN) is proposed and designed. Firstly, a novel emotional neural network which can approximate the uncertainties in nonlinear systems is constructed and introduced. Meanwhile, in order to optimize the network structure and reduce the computing burden, a novel spiking-based self-organizing mechanism is added. Then the FOFTSMC is designed for second-order general nonlinear systems, and the stability and finite time convergence is proved by Lyapunov theory. Besides, the FOFTSMC and SOENN are combined to form the final control scheme, and adaptive laws of the parameters are also designed. Finally, inverted pendulum and active power filter (APF) are selected as the research objects to carry out a series of simulations and experiments to validate and highlight the effectiveness and superiority of the proposed control scheme.