Fuzzy‐approximator‐based adaptive controller design using Nussbaum‐type function

Abstract

While the Takagi–Sugeno (T‐S) fuzzy model is widely used as a model to design a controller for a system to be controlled, there is a gap, which in this paper is referred to as uncertainty, between the T‐S fuzzy model and the system. The uncertainty is considered here in an effort to improve the control system performance. Though the basic idea to address the uncertainty in this paper is to employ a frequently used approach that utilizes a fuzzy approximator, the relevant parameters are tuned by novel adaptive laws with the help of the Nussbaum‐type function. Consequently, the closed‐loop control system is able to be asymptotically stable. In addition, simulations are provided to demonstrate the effectiveness of the approaches proposed. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Fuzzy adaptive control of a multimachine system with single inverter supply

“…The choice of the model for the speed loop focused on the transfer function of two motors, which links the mechanical speed to the electromagnetic torque (Equation ). For the current loop, the model is equivalent to the transfer function in order to define the parameters of the current controllers …”

“…For the current loop, the model is equivalent to the transfer function (35) in order to define the parameters of the current controllers. 32 The following model of the MSCS is obatined as follows:…”

“…The expressions (32) and (33) are the behavior models of the angular speed and the stator currents that are used in the proposed control.…”