Maximum Power Point Tracking Using Model Reference Adaptive Control

This paper proposes an adaptive control architecture for maximum power point tracking (MPPT) in photovoltaic systems. MPPT technologies have been used in photovoltaic systems to deliver the maximum available power to the load under changes of the solar insolation and ambient temperature. To improve the performance of MPPT, this paper develops a two-level adaptive control architecture that can reduce complexity in system control and effectively handle the uncertainties and perturbations in the photovoltaic systems and the environment. The first level of control is ripple correlation control (RCC), and the second level is model reference adaptive control (MRAC). By decoupling these two control algorithms, the system achieves MPPT with overall system stability. This paper focuses mostly on the design of the MRAC algorithm, which compensates the underdamped characteristics of the power conversion system. The original transfer function of the power conversion system has time-varying parameters, and its step response contains oscillatory transients that vanish slowly. Using the Lyapunov approach, an adaption law of the controller is derived for the MRAC system to eliminate the underdamped modes in power conversion. It is shown that the proposed control algorithm enables the system to converge to the maximum power point in milliseconds.