Maximum power point tracking using adjustable gain based model reference adaptive control

This paper aims to develop an adjustable gain-based model reference adaptive control (AG-MRAC) scheme for maximum power point tracking (MPPT) in photovoltaic (PV) systems. To ensure a fast convergence speed with guaranteed transient performance and overall system stability of the MPPT under rapidly changing environmental conditions, a 2-level control scheme has been proposed. The first level of control is the conventional ripple correlation control (RCC), which is used to obtain a ripple-free optimal duty cycle in the steady-state. This also serves as input for the second level of control, which is the proposed AG-MRAC controller. The conventional high-static adaptation gain MRAC provides guaranteed transient performance in MPPT. However, a high adaptation gain circumvents the adverse effects on the system stability and robustness. Moreover, in PV systems, when the environmental conditions are rapidly changing, the requirement gain depends on the magnitude of the error. Therefore, a fixed high gain controller does not provide a complete solution to the dynamic behavior of non-linear PV systems under rapidly changing environmental conditions. This paper attempts to overcome these issues using the proposed AG-MRAC architecture, where the adaptation gain is adjusted as a function of the tracking error, which is caused by variations in environmental conditions. A mathematical model of the proposed AG-MRAC has been developed and its stability has been verified using Lyapunov theory. To check the effectiveness of the proposed control scheme, simulation and experimental models have been developed for validation. In addition, a performance comparison has been done with recent similar works.