Event-triggered adaptive NNs tracking control of three-phase PWM rectifiers under random disturbances

This paper is concerned with the problem of tracking control of three-phase pulsewidth-modulation rectifiers under random disturbances. According to power theory, the effect of random disturbances to three-phase rectifiers is interpreted from the perspective of output voltage or reactive power disturbed by colored noises. Thus, a random model of three-phase pulsewidth-modulation rectifiers in a d-q frame is constructed. Then, to deal with the uncertainties of parameters and unknown nonlinear functions, a radial basis function neural networks approach in combination with adaptive technique is applied to design an event-triggered state feedback tracking controller. By using random Lyapunov stable theory, it is proven that the states of the closed-loop system are bounded in probability and the tracking error can be rendered arbitrarily small by adjusting related parameters appropriately. Moreover, the Zeno behavior is excluded. Finally, simulation results are proposed to verify the validity of the proposed control strategy.

Automated summary

This paper investigates the problem of tracking control for three-phase pulsewidth-modulation rectifiers under random disturbances. By constructing a random model and designing a controller, it is proven that the states of the closed-loop system are bounded and the tracking error can be controlled by adjusting parameters.