A nonlinear zeroing neural network and its applications on time-varying linear matrix equations solving, electronic circuit currents computing and robotic manipulator trajectory tracking

Zeroing neural network has proved its powerful abilities and efficiency in solving various time-varying problems, and its convergence and robustness have been deeply studied in recent years. To further enhance its convergent speed and robustness for time-varying linear matrix equation solving, a nonlinear zeroing neural network (NZNN) with a new activation function is proposed in this paper. The superiority of the proposed NZNN model is theoretically validated through rigorous mathematical analysis. Besides, the proposed NZNN model is applied to time-varying matrix inversion solving, static and dynamic voltage electronic circuit currents computing, which further verifies its practical abilities for engineering oriented applications.

Automated summary

In this paper, a new nonlinear zeroing neural network (NZNN) model is proposed to enhance the convergent speed and robustness for time-varying linear matrix equation solving. The superiority of the proposed NZNN model is theoretically validated through rigorous mathematical analysis, and its practical abilities are further verified through engineering oriented applications.