An improved 2-level MPPT scheme for photovoltaic systems using a novel high-frequency learning based adjustable gain-MRAC controller

Abstract

Under rapidly changing environmental conditions, the model reference adaptive control (MRAC) based MPPT schemes need high adaptation gain to achieve fast convergence and guaranteed transient performance. The high adaptation gain causes high-frequency oscillations in the control signals resulting in numerical instability and inefficient operation. This paper proposes a novel high-frequency learning-based adjustable gain MRAC (HFLAG-MRAC) for a 2-level MPPT control architecture in photovoltaic (PV) systems to ensure maximum power delivery to the load under rapidly changing environmental conditions. In the proposed 2-level MPPT control architecture, the first level is the conventional ripple correlation control (RCC) that yields a steady-state ripple-free optimum duty cycle. The duty cycle obtained from the first level serves as an input to the proposed HFLAG-MRAC in the second level. In the proposed adaptive law, the adaptation gain varies as a function of the high-frequency ripple content of the tracking error. These high-frequency contents are the difference between the tracking error and its low-pass filtered version representing the fluctuations in output due to rapid changes in the environmental conditions. Thus, adjusting the adaptation gain by high-frequency content of the tracking error ensures fast convergence, guaranteed transient performance, and overall system stability without needing high adaptation gain. The adaptive law of the proposed HFLAG-MRAC is derived using the Lyapunov theory. Simulation studies, experimental analysis, and performance comparison with recent similar work validate the effectiveness of the proposed work.

A novel robust maximum power extraction framework for sustainable PV system using incremental conductance based MRAC technique

“…Figure 24 shows the PV current vs. load current, and Figure 25 shows the PV voltage vs. load voltage in all the states. Table 2 36) and (37).…”

“…MRAC architecture aims to critically dampen reaction. It is an adaptive controller that matches the plant model's to reference model's response even if plant parameters vary or are unclear 37 . Figure 9 depicts the block representation of the MRAC model.…”

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

“…[26]. A small-signal equivalent circuit is assumed to simplify the study of transient response as indicated in [27]. Figure 5 displays the small-signal equivalent circuit of PV.…”