Adaptive Controller of the Major Functions for Controlling a Drive System with Elastic Couplings

Abstract

In any drive system, there are always couplings between the motor and the load. Since the hardness of these couplings is finite, they have elastic properties, causing unwanted vibration and negatively affecting system quality. When the couplings are springs with nonlinear characteristics, control is particularly difficult because it is very difficult or impossible to define the parameters of the controlled object. To solve these difficulties, this article proposes an adaptive controller of the major functions for controlling a drive system with nonlinear elastic couplings of unidentified parameters. For the proposed control system, we measure the response speed of the object, use a Luenberger observer to estimate the state variables of the system, and use an adaptive controller to control the system. The experimental results demonstrate that the control object can be controlled without knowing the parameters: the control quality of the system is very good, close to that of a system with a hard coupling, there is no vibration or overshoot, and the transition time is small.

Fuzzy Adaptive Type II Controller for Two-Mass System

“…Adaptive systems can be distinguished as a third group. In general, two types of adaptive control are mentioned in the literature [27][28][29][30][31][32][33][34][35][36]. The first one is called indirect adaptive control.…”

“…The second approach is called direct adaptive control, in which the parameters of the controller are changed directly, due to the changes of the tracking error (specified as output between the desired trajectory and real output of the plant) [28][29][30][31][32][33][34][35][36][37][38]. For linear systems the suitable solution could be a classical PI controller.…”

“…In the literature, different types of controllers are proposed. In [33][34][35][36][37] NN (neural networks) based approaches are implemented. A comparison of four different types of NN controllers is presented in [34].…”

“…In [33][34][35][36][37] NN (neural networks) based approaches are implemented. A comparison of four different types of NN controllers is presented in [34]. The problems related to the selection of the initial parameters and learning factors in an adaptation algorithm are discussed.…”

The optimal control system of the ship based on the linear quadratic regular algorithm

“…This is a controller with a simple structure, but the quality of the control system is not high. Recently, the development of informatics and electronic technology let the scientist to set up the advanced control theory for ship, such as fuzzy control [5][6][7], the model predictive control [8][9][10], the sliding mode control [11,12], the backstepping technique [13,14], the adaptive control [15,16], etc. The research [17] has proposed the control system of the ship in order for the motion trajectory to follow with the desired trajectory based on the backstepping technique.…”