Auto-Tuning Process of State Feedback Speed Controller Applied for Two-Mass System

Abstract

The state feedback controller is increasingly applied in electrical drive systems due to robustness and good disturbance compensation, however its main drawback is related to complex and time consuming tuning process. It is particularly troublesome for designer, if the plant is compound, nonlinear elements are taken into account, measurement noise is considered, etc. In this paper the application of nature-inspired optimization algorithm to automatic tuning of state feedback speed controller (SFC) for two-mass system (TMS) is proposed. In order to obtain optimal coefficients of SFC, the Artificial Bee Colony algorithm (ABC) is used. The objective function is described and discussed in details. Comparison with analytical tuning method of SFC is also included. Additionally, the stability analysis for the control system, optimized using the ABC algorithm, is presented. Synthesis procedure of the controller is utilized in Matlab/Simulink from MathWorks. Next, obtained coefficients of the controller are examined on the laboratory stand, also with variable moment of inertia values, to indicate robustness of the controller with optimal coefficients.

State Feedback Speed Control with Periodic Disturbances Attenuation for PMSM Drive

“…The minimization of speedtracking error defined in the performance index would result in high values of controller coefficients in order to achieve a high dynamic, which causes dangerous noises amplification. The most common methods used to prevent such behaviour are based on additional part in performance index aimed at minimizing the derivative of the control signal [17,18]. This approach requires expert knowledge and trial-and-error procedure to determine the proper gain coefficient for derivative limitation, which ensures satisfactory system response and safe system operation.…”

“…It requires a definition of a number of control parameters, listed in Table 1. These parameter selections are based on parameters used to solve similar optimization problems [17,18]. It should be noted that the optimization algorithm requires a definition of nine parameters, where three of them are related to the dimension of optimized parameters (D) and the size of colony (NP), where the dimension is a bounded value related directly to the optimized problem.…”

“…It allows to minimize the impact of periodic disturbances on the angular velocity of the drive. The literature review [2,14,17,18] indicates that no former works related to application of auto-tuned and constrained SFC for attenuation of periodic disturbances in a PMSM drive system have been presented before. The novelty of the proposed solution is the adaptation of a meta-heuristic optimization algorithm for attenuation of periodic disturbances in a PMSM drive system with a state feedback controller.…”

Modern Electrical Drives: Trends, Problems, and Challenges

“…The article by Szczepanski et al [4] describes an application of a nature-inspired metaheuristic optimization algorithm in the controller's auto-tuning. To fulfill the requirements related to the precise control of a complex plant, the original objective function minimized during the automatic synthesis process of the controller has been proposed.…”

“…Very often, they are multidisciplinary works. In this Special Issue, 10 manuscripts were published that deal with the following topics: control strategies for different types of electrical motors [1][2][3], estimations of non-measurable states and parameters [3], sensorless control of electrical drives [1,2], the application of advanced control methodologies for high performance control of electrical drives [4][5][6], diagnoses, monitoring, and prognoses in electrical drives [7][8][9][10], and control of complex mechatronic systems, while taking the mechanical part of the system into account [3,4,6].…”