Maximum power extraction framework using robust fractional-order feedback linearization control and GM-CPSO for PMSG-based WECS

Abstract

The most important issue in the use of wind energy conversion systems is to ensure maximum power extraction in terms of efficiency. Therefore, maximum power point tracking algorithms are as important as the maximum power point tracking controller. In this study, maximum power extraction frameworks operating the state-of-the-art optimization methods are presented for permanent magnet synchronous generator–based wind energy conversion system. These frameworks consist of a Gauss map–based chaotic particle swarm optimization and a hybrid maximum power point tracking approach that combines feedback linearization technique with fractional-order calculus. The feedback linearization control strategy can fully decouple and linearize the original state variables of the nonlinear system and thus provide an optimal controller crossing wide-range operating conditions. The objective is to maintain the tip speed ratio at its optimal value, which implies the use of a rotational speed loop. The method is based on the feedback linearization technique and the fractional control theory. Gauss map–based chaotic particle swarm optimization, which is a remarkable and recent optimization technique, is utilized to achieve optimum coefficients to efficiently ensure the maximum power point tracking operation in here. A simulation study is carried out on a 3-kW wind energy conversion system to show the effectiveness of the proposed control scheme.

Fractional-Fuzzy PID Control Approach of Photovoltaic-Wire Feeder System (PV-WFS): Simulation and HIL-Based Experimental Investigation

“…where a and t are the limits of the FO operator, while α is the order of integration or differentiation (α ∈ ℝ). Liouville-Riemann, Caputo, and Letnikov-Grunwald descriptions of FO calculus are the ones that are most often used in FO systems [55]. FO systems are differ from IO systems in their behavior, where FO systems may have roots in the right half s-plane and can be remain stable.…”

“…To develop FO functions in real or simulation works, representation using IO transfer functions must be utilized. The Oustaloup's recursive transfer function is one of the common approximation tools, which utilizes recursive distribution of K constant, N zeros and N poles [55]. Thus, in this study, the higher-integer order filter is utilized for approximation of FO systems as expressed by Eq.…”

“…where, ωl and ωh are the low and high frequencies bands [54][55][56]. In this article, the frequency band is utilized as ω = [10 -3 ,10 3 ] rad/s, and the 5th order Oustaloup's recursive transfer function is exploited.…”

Combined adaptive neural network and regressor‐based trajectory tracking control of flexible joint robots

“…An important observation is that the implementation of the feedback linearization-based controller (35), with q md in (36), requires that the desired link position q ld (t ) to be at least four times continuously differentiable. Another observation is that the desired rotor velocity qmd and the desired rotor acceleration qmd cannot be estimated as discussed above if the model parameters are unknown or uncertain.…”

Comparison between ABC and ACO: Tunning of On-Off MPPT for wind systems

“…Various power optimization methods have been used for different levels of the conversion chain, the objective of which is to obtain maximum power by increasing the efficiency of the wind turbine (Errami et al, 2013). Different Maximum Power Point Tracking (MPPT) controls have been used to extract maximum power such as (Dursun et al, 2020; Kahla et al, 2020). Each technique of the latter is characterized by a term of cost, speed of convergence, complexity, popularity, required sensors, implementation, and other criteria(Hassani et al, 2011).…”