Suboptimal control of magnetic levitation (Maglev) system

Author(s):  
Avadh Pati ◽  
Richa Negi
Author(s):  
Feng Tian ◽  
Mark Nagurka

A magnetic levitation (maglev) system is inherently nonlinear and open-loop unstable because of the nature of magnetic force. Most controllers for maglev systems are designed based on a nominal linearized model. System variations and uncertainties are not accommodated. The controllers are generally designed to satisfy gain and phase margin specifications, which may not guarantee a bound on the sensitivity. To address these issues, this paper proposes a robust control design method based on Quantitative Feedback Theory (QFT) applied to a single degree-of-freedom (DOF) maglev system. The controller is designed to successfully meet the stability requirement, robustness specifications, and bounds on the sensitivity. Experiments verify that the controller maintains stable levitation even with 100% load variation. Experiments prove that it guarantees the transient response design requirements even with 100% load change and 39% model uncertainties. The QFT control design method discussed in this paper can be applied to other open-loop unstable systems as well as systems with large uncertainties and variations to improve system robustness.


2012 ◽  
Vol 546-547 ◽  
pp. 992-996
Author(s):  
Chun Fang Liu ◽  
Bin Zang ◽  
Tong Wang

The maglev system is a typical nonlinear system, it is difficult to get the best control effect only by nonlinear control method. At first, the maglev system is linearized in this paper, for the classic PID control magnetic levitation system which exists the contradiction between fast and overshoot .This paper adopts the nonlinear tracking-differentiator-based PID controller to control the maglev system. Finally simulation results show that the nonlinear PID controller has fast response speed, no overshoot, and strong robustness in controlling the maglev system.


2014 ◽  
Vol 511-512 ◽  
pp. 1039-1043
Author(s):  
Qing Zhen Wang ◽  
A Ming Hao ◽  
Zhi Qiang Wang

Combining with the principle of permanent magnetic and electromagnetic suspension, we can establish its mathematical model. Maglev system is a typical nonlinear system. Simulation model is built based on fuzzy control in matlab by combining the advantages of fuzzy control. By comparing the simulation results with PID, the simulation results show that fuzzy control can make the magnetic levitation system has better dynamic performance and steady-state performance.


Author(s):  
Tran Huu Luat ◽  
◽  
Yong-Tae Kim

In this paper, the levitation control method of a MIMO Magnetic Levitation (Maglev) transportation system with 3-DOF is presented. Fluctuations of magnetic poles cause the Maglev system to become critically unstable. We propose a design method of the MIMO Maglev controller based on SISO Maglev control technology to correct the suspension and compensate for the effect of rotational motions. In addition, a force loop controller is designed for placement in front of each sub-controller of an electromagnet for stability improvement. The proposed control method is evaluated using simulations and real experiments using the developed Maglev transportation system.


2019 ◽  
Vol 42 (3) ◽  
pp. 543-550
Author(s):  
Vimala Kumari Jonnalagadda ◽  
Vinodh Kumar Elumalai ◽  
Shantanu Agrawal

This paper presents the current cycle feedback iterative learning control (CCF-ILC) augmented with the modified proportional integral derivative (PID) controller to improve the trajectory tracking and robustness of magnetic levitation (maglev) system. Motivated by the need to enhance the point to point control of maglev technology, which is widely used in several industrial applications ranging from photolithography to vibration control, we present a novel CCF-ILC framework using plant inversion technique. Modulating the control signal based on the current tracking error, CCF-ILC reduces the dependency on accurate plant model and significantly improves the robustness of the closed loop system by synthesizing the causal filters to counteract the effect of model uncertainty. To assess the stability, we present a maximum singular value based criterion for asymptotic stability of linear iterative system controlled using CCF-ILC. In addition, we prove the monotonic convergence of output sequence in the neighbourhood of reference trajectory. Finally, the proposed control framework is experimentally validated on a benchmark magnetic levitation system through hardware in loop (HIL) testing. Experimental results substantiate that synthesizing CCF-ILC with the feedback controller can significantly improve the trajectory tracking and robustness characteristics of maglev system.


2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Dini Wang ◽  
Fanwei Meng ◽  
Shengya Meng

Linearized model of the system is often used in control design. It is generally believed that we can obtain the linearized model as long as the Taylor expansion method is used for the nonlinear model. This paper points out that the Taylor expansion method is only applicable to the linearization of the original nonlinear function. If the Taylor expansion is used for the derived nonlinear equation, wrong results are often obtained. Taking the linearization model of the maglev system as an example, it is shown that the linearization should be carried out with the process of equation derivation. The model is verified by nonlinear system simulation in Simulink. The method in this paper is helpful to write the linearized equation of the control system correctly.


2019 ◽  
Vol 9 (16) ◽  
pp. 3263 ◽  
Author(s):  
Xianze Xu ◽  
Chenglin Zheng ◽  
Fengqiu Xu

Magnetic levitation technology shows promise for realizing multiple degrees of free precision motion for modern manufacturing, as the bearing and guiding parts are not used. However, motion decoupling in a magnetically levitated (maglev) system is difficult because it is hard to derive accurate magnetic force and a torque model considering the translation and rotation in all axes. In this work, a magnetic levitation rotary table that has the potential to realize unlimited rotation around the vertical axis and a relatively long stroke in the horizontal plane is proposed and analyzed, and the corresponding real-time numerical decoupling method is presented. The numerical magnetic force and torque model solves the current to magnetic force and torque transformation matrix, and the matrix is used to allocate the exact current in each coil phase to produce the required motion in the magnetically levitated (maglev) system. Next, utilizing a high-level synthesis tool and hardware description language, the proposed motion-decoupling module is implemented on a field programmable gate array (FPGA). To realize real-time computation, a pipelined program architecture and finite-state machine with a strict timing sequence are employed for maximum data throughput. In the last decoupling module of the maglev system, the delay for each sampling point is less than 200 μ s. To illustrate and evaluate real-time solutions, they are presented via the DAC adapter on the oscilloscope and stored in the SD card. The error ratios of the force and torque results solved by the numerical wrench model were less than 5 % and 10 % using the solutions from the boundary element method (BEM) program package RadiaTM as a benchmark.


Author(s):  
Akira Nakagawa ◽  
Satoshi Matsuda

In 2005 the Central Japan Railway Company introduced new technological breakthroughs that will enhance revenue service on its superconducting magnetic levitation (maglev) system. This paper covers developments in both basic and applied research, discusses new equipment, and reviews the status of the system's running tests. Superconducting maglev has been developed to be applied to the Chuo Shinkansen, a proposed artery between Tokyo and Osaka. Its basic performance and various functions were already confirmed by 2000 through running tests done on the Yamanashi Maglev Test Line; running tests continue to be conducted to verify the train's durability and reliability and to upgrade its performance with new technologies. One immediate goal of these tests is to finalize the technology necessary for revenue service by March 2005.


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