This study uses a sliding mode control (SMC) in a generator-based exercise equipment (GBEE) with nonlinear P-V characteristic curves. A P-V characteristics curve can be influenced by varying the pedaling speed of the generator. The traditional maximum power point tracking (MPPT) control method is used with perturb and observe algorithms (P&O), extremum seeking control (ESC), etc. However, these control methods are not robust enough for control. SMC is created by two pattern methods for robustness control, approaching and sliding conditions. However, SMC allows infinite high-frequency switching of the sign function. If the sign function is used to switch the converter, it will cause the converter and switch life to be cut short, and also to form high frequency noise. Therefore, this study proposes an extension theory for an intelligent control method that will effectively improve conversion efficiency and responsiveness. This study compares generator input current waveforms for fast Fourier transform (FFT) for three different control methods. Finally, using simulation validates the stability and FFT analysis with power simulation (PSIM) software. The results of upgrading overall efficiency are about a 5% increase in efficiency and a faster response speed of about 0.5 s. The amount of generator input current harmonic is greatly reduced.