Finite-Time Disturbance Observer of Nonlinear Systems

In practical applications, for highly nonlinear systems, how to implement control tasks dynamic systems with uncertain parameters is still a hot research issue. Aiming at the internal parameter fluctuations and external unknown disturbances in system, this paper proposes an adaptive terminal sliding mode (ADTSMC) based on finite-time disturbance observer (FTDO) systems. A designed compensate uncertainties (DTSMC) method developed achieve finite time convergence weaken system chattering. Moreover, dual hidden layer recurrent neural network (DHLRNN) estimator proposed approximate gain, so that switching item gain not overestimated optimal value obtained. Finally, simulation experiments of active power filter model verify ADTSMC has better steady-state dynamic-steady compensation effects least 1% THD reduction presence load compared simple DTSMC law.