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In this study, a multilevel inverter was designed and implemented to operate a stand-alone solar photovoltaic system. The proposed system uses pulse-width modulation (PWM) in the multilevel inverter to convert DC voltage from battery storage to supply AC loads. In the PWM method, the effectiveness of eliminating low-order harmonics in the inverter output voltage is studied and compared to that of the sinusoidal PWM method. This work also uses adaptive neuro fuzzy inference (ANFIS) to predict the optimum modulation index and switch angles required for a five level cascaded H-bridge inverter with improved inverter output voltage. The data set for the ANFIS-based analysis was obtained with the Newton-Raphson (NR) method. The proposed predictive method is more convincing than other techniques in providing all possible solutions with any random initial guess and for any number of levels of a multilevel inverter. The simulation results prove that the lower-order harmonics are eliminated using the optimum modulation index and switching angles. An experimental system was implemented to demonstrate the effectiveness of the proposed system.