Fractional order controllers tuning strategy for permanent magnet synchronous motor servo drive system based on genetic algorithm–wavelet neural network hybrid method

Abstract

In this paper, a novel tuning strategy for the fractional order proportional integral and fractional order [proportional integral] controllers is proposed for the permanent magnet synchronous motor servo drive system. The tuning strategy is based on a genetic algorithm–wavelet neural network hybrid method. Firstly, the initial values of the control parameters of the fractional order controllers are selected according to a new global tuning rule, which is based on the genetic algorithm and considers both the time- and frequency-domain specifications. Secondly, the wavelet neural network is utilized to update the control parameters based on the selected initial values in an online manner which improves the capability of handling parameter variations and time-varying operating conditions. Furthermore, to improve the computational efficiency, a recursive least squares algorithm, which provides information to the wavelet neural network, is used to identify the permanent magnet synchronous motor drive system. Finally, experimental results on the permanent magnet synchronous motor drive system show both of the two proposed fractional order controllers work efficiently, with improved performance comparing with their traditional counterpart.

Graphical tuning method of FOPID controllers for fractional order uncertain system achieving robust ‐stability

“…Following the line of Algorithm 5.1, we can obtain the sufficient region shown in Figure 11. The green-line surrounded area is the sufficient -stabilizing region that is obtained by using Theorem 5.3 (2). It is also noted that the blue-line surrounded area is the complete -stabilizing region that is obtained by Theorem 5.1.…”

“…An FOPID controller is a generalization of a conventional integer proportional integral derivative (PID) controller. It can afford more flexibility in controller design because of its additional fractional order hence possibly achieve a better control performance . Nevertheless, this also implies that the parameter tuning of FOPID controllers is much more complex than integer PID controllers.…”

Model-free tuning strategy of fractional-order PI controller for speed regulation of permanent magnet synchronous motor

“…Test results under Case 2 ( J e =1.108×10 −3 kg·m 2 + 1.088×10 −3 kg·m 2 ) have been applied to evaluate the performance of the proposed method with external load disturbances. The existing model-based method (Zheng et al, 2014) is added for comparison, which is based on the identification of accurate model of (1). As shown in Figures 10 and 11, the tracking errors are limited to stabilized regions around zero under the comparison controllers.…”

Adaptive Fractional Order PI Controller Design for a Flexible Swing arm System Via Enhanced Virtual Reference Feedback Tuning

“…Research activities are focused on optimizing FOPI controllers to achieve the desired performance specified in both time‐domain and frequency‐domain . Many efforts have been made to develop parameter tuning methods for the FOPI controller as an extension of classical control theory, including evolutionary algorithm , neural network algorithm , Bode shaping‐based design methods , model reference control method , and fuzzy approach . These tuning techniques require the system model information to update the control parameters, like dynamic linear models and transfer function models .…”