Intelligent power control of wind conversion system based on Takagi–Sugeno fuzzy model

Abstract

This paper comes up with a novel fuzzy control design for a wind conversion system (WCS). To do this, a boost converter is employed to adjust the rectified voltage under different wind speed levels. Initially, the boost converter model is well presented via the Takagi-Sugeno approach. Then, a T-S fuzzy controller is designed to promptly calculate the duty cycle required for an optimal power operation. Afterward, the optimal DC current is determined and then transferred to the reference model to instantly determine the desired trajectories. These latter should be preserved so as to reach the maximum power. Following that, linear matrix inequalities (LMIs) are also used to guarantee the stability analyses and the H performance. Finally, the sound performance and the validity of the suggested control schema are both proved by a numerical and some experimental results.

Coordinated operation of fuzzy‐based TCSC and SMES for low‐frequency oscillation damping in interconnected power systems

“…Fuzzy logic control (FLC) has emerged as a most prominent methodologies for designing complex controllers, especially for complicated nonlinear systems with uncertain or unmodeled dynamics. These are the primary characteristics that render them useful for control systems 50–52 : They can be employed to characterize sophisticated, nonlinear, multidimensional models that are challenging by conventional mathematical techniques. They provide reliable and robust performance in various operating conditions, in addition to implementation and flexibility in design. They are capable of handling systems with incorrect or uncertain dynamics, in addition to systems with parameter uncertainties. They encourage the implementation of insights and expertise of the designers, unlike all other intelligent controllers. …”

“…Fuzzy logic control (FLC) has emerged as a most prominent methodologies for designing complex controllers, especially for complicated nonlinear systems with uncertain or unmodeled dynamics. These are the primary characteristics that render them useful for control systems [50][51][52] :…”

State-Difference Feedback Control for Discrete-Time Takagi–Sugeno Fuzzy Descriptor Systems with Parameter Uncertainties and External Noises

“…Furthermore, the method can be combined with traditional control theory, exploiting the advantages of both approaches, and allowing for the design of controllers capable of handling complex systems while providing stability and analysis tools. T-S FS are used in many fields, including robotic arms, pattern recognition, and power systems [9,10]. In the growing field of control systems and mathematical modeling, T-S FS have been extended to descriptor systems [11,12].…”

“…(1) Compared with the way that the system is described in [9,10], the proposed descriptor system can effectively describe nonlinear phenomena. Each rule in the T-S model corresponds to a local linear approximation of the system dynamics within a specific region of the input space.…”