Performances Comparison for a Rotating Shaft Suspended by 4‐Axis Radial Active Magnetic Bearings via μ‐Synthesis, Loop‐Shaping Design, and Sub(H)_∞with Uncertainties

Abstract

The control systems applied on active magnetic bearing are several. A perfect levitation is characterized by maintaining the operating point condition that is characterized by the center of stator coincident with the geometric center of shaft. The first controller implemented for this purpose is PID controller that is characterized by an algorithm that leads the amplifier to produce control current until the operating point condition is not reached, this is obtained by an integration operator. The effect of an integrator is essential but not necessary for a centered levitation for example in the robust control characterized by a dynamic model depended on plant of system so that it depends on angular speed as LQR controller does. In LQR there is not integrator so there is not a perfectly centered section of shaft with center of stator. On contrary PID controller does not depend on angular speed and it can be easily implemented according some simple rules. Predictive control is another interesting controller characterized by a multiple controller operating in different condition in order to get the minimum of cost function, but also in this case the angular speed is introduce for the same reason discussed before.

An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

“…In [18] the problem is dealt by using a Linear Quadratic Regulator (LQR) and introducing a parameter denoted as yaw index that accounts for the rate of change of the sideslip angle. Interesting comparisons of feedback control techniques are presented in [28,29].…”

System Identification and Robust Control of Multi-Input Multi-Output Active Magnetic Bearing Systems

“…In order to scale up the errors around the two resonant modes, six variables are defined. These parameters are mainly the lower and upper frequency ranges of interest ([ω 1−start , ω 1−end ], and [ω 2−start , ω 2−end ]), and their corresponding scaling factors (α and β) as shown in (16). The optimum value of (α and β) are to be found by the GA to heavily penalize the fitting error in a particular range of frequencies where the modeling accuracy is important.…”

“…With the growing interest in the applications of fast and precise AMBs, there is a demand for developing advanced controllers that ensure robust performance of such systems in the presence of unmodeled dynamics and unknown external disturbances [9]- [12]. Although several works can be found on the analytical modeling and simulation of robust controllers on AMBs [13]- [16], system identification and real-time robust control of AMBs is a relatively recent development [17]- [26]. However, the results presented in the recent works have many shortcomings to consider this problem as solved.…”

Fixed-time supper twisting disturbance observer and sliding mode control for a secure communication of fractional-order chaotic systems

“…The proposed stability was used to design the sliding mode controller. Herein, the DO was used to improve the robustness of synchronization control, which differs to the mentioned robustness controller base on the H∞ in Barbaraci and Mariotti (2011). The contributions of this paper are listed below.1.…”