scholarly journals Design of Robust Control System of Magnetic Suspension and Balance System through Harmonic Excitation Simulation

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 304
Author(s):  
Dong-Kyu Lee
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Power Supply ◽  
Test Section ◽  
Test Object ◽  
Control Algorithm ◽  
Magnetic Suspension ◽  
Electric Power Supply ◽  
Balance System ◽  
Adaptive Control Algorithm

The magnetic suspension and balance system (MSBS) uses magnetic force and moment to precisely control the movement of the test object located at the center of the test section without mechanical contact, and at the same time measure the external force acting on the test object. If such an MSBS is installed around the test section of the wind tunnel so that the position and attitude angle of the test object follow the harmonic function, various vibration tests can be performed on structures subjected to aerodynamic loads without the influence of the mechanical support. Because the control force and moment in the MSBS is generated by a number of electromagnets located around the test section, it is necessary to apply the adaptive control algorithm to the position and attitude control system so that the experiment can be carried out stably despite the sudden performance change of each electromagnet and electric power supply. In this study, a fault-tolerant position and attitude angle control system was designed through an adaptive control algorithm, and the effectiveness was verified through simulation under the condition that the electric power supply of MSBS failed.

scholarly journals REPETITIVE ADAPTIVE CONTROL OF NONLINEAR UNCERTAIN PLANT WITH INPUT SATURATION

2021 ◽  
pp. 122-135
Author(s):  
E.A. Shelenok ◽  
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Control Algorithm ◽  
Reference Model ◽  
Input Saturation ◽  
Adaptive Control System ◽  
Bounded Disturbances ◽  
Adaptive Control Algorithm ◽  
Fast Acting ◽  
Nonlinear Plant

The article proposes solution to the problem of synthesizing adaptive control algorithm for dy-namic T-periodic nonlinear plant operating under conditions of structural and parametric uncer-tainty, in the presence of input restrictions and constant bounded disturbances. The hyperstabil-ity criterion, L-dissipativity conditions, fast-acting filter-correctors, and an implicit reference model are used as the methods for synthesis of repetitive adaptive control system.

scholarly journals Fully Automatic Operation Algorithm of Urban Rail Train Based on RBFNN Position Output Constrained Robust Adaptive Control

Algorithms ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 264
Author(s):  
Junxia Yang ◽  
Youpeng Zhang ◽  
Yuxiang Jin
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Control Algorithm ◽  
Ride Comfort ◽  
Robust Adaptive Control ◽  
Automatic Operation ◽  
Urban Rail ◽  
Fully Automatic ◽  
Robust Adaptive ◽  
Adaptive Control Algorithm

High parking accuracy, comfort and stability, and fast response speed are important indicators to measure the control performance of a fully automatic operation system. In this paper, aiming at the problem of low accuracy of the fully automatic operation control of urban rail trains, a radial basis function neural network position output-constrained robust adaptive control algorithm based on train operation curve tracking is proposed. Firstly, on the basis of the mechanism of motion mechanics, the nonlinear dynamic model of train motion is established. Then, RBFNN is used to adaptively approximate and compensate for the additional resistance and unknown interference of the train model, and the basic resistance parameter adaptive mechanism is introduced to enhance the anti-interference ability and adaptability of the control system. Lastly, on the basis of the RBFNN position output-constrained robust adaptive control technology, the train can track the desired operation curve, thereby achieving the smooth operation between stations and accurate stopping. The simulation results show that the position output-constrained robust adaptive control algorithm based on RBFNN has good robustness and adaptability. In the case of system parameter uncertainty and external disturbance, the control system can ensure high-precision control and improve the ride comfort.

Sign in / Sign up

Export Citation Format

Share Document