Passivity ANFIS-Based Control for an Intelligent Compact Multilevel Converter

This article proposes a passivity method synthesized by an adaptive neuro fuzzy inference system (ANFIS) to control a grid-tied nine-level packed E-cell (PEC9) inverter. PEC9 is an optimized components count of single-phase, single-dc-source, compact multilevel converter with an appealing feature of dc capacitors horizontal extension. Indeed, PEC9 forms a single auxiliary dc-bus to actively balance its voltages so as grid-tied controller would not be charge of capacitors voltages balancing. Hence, the proposed intelligent-based passivity control (IPC) is designed using only the dynamical model of the PEC9 inverter current. The zero dynamics of state variable errors are obtained and a damping coefficient matrix is presented to theoretically analyze the convergence rate of PEC9 inverter currents under the proposed control functions. In addition, various operating margins of damping coefficients are inquired. So, using the margins, a trained ANFIS as an online estimator tracks the damping injections. It precisely regulates the damping coefficients in unstable conditions; thus, the excellent PEC9 inverter operation is guaranteed. Experiments and simulations validate high reliable performance of the proposed IPC technique under various grid-tied operational conditions.

Automated summary

This article proposes a passivity method using an adaptive neuro fuzzy inference system (ANFIS) to control a grid-tied nine-level packed E-cell (PEC9) inverter. The method is able to balance the voltages of PEC9 and ensure its reliable operation. Experiments and simulations validate the high reliability of the proposed technique under various grid-tied operational conditions.