scholarly journals Enhanced Nonlinear PID Controller for Positioning Control of Maglev System

2021 ◽  
Author(s):  
Shin-Horng Chong ◽  
Roong-Soon Allan Chan ◽  
Norhaslinda Hasim
Keyword(s):  
Transient Response ◽  
Magnetic Levitation ◽  
Feedforward Control ◽  
Design Procedure ◽  
Deep Understanding ◽  
Model Parameters ◽  
Pd Controller ◽  
Positioning Control ◽  
Nonlinear Pid Controller ◽  
Magnetic Levitation System

Magnetic levitation (maglev) is a way of using electromagnetic fields to levitate objects without any noise or the need for petrol or air. Due to its highly nonlinear and unstable behavior, numerous control solutions have been proposed to overcome it. However, most of them still acquire precise dynamic model parameters, or deep understanding of control theory. To account the complexity in the design procedure, a practical controller consists of classical and modern control approaches are proposed. This chapter presents a practical controller for high positioning performance of a magnetic levitation system. Three strategies of the proposed controller where the PI-PD controller is to enhance transient response, the model-based feedforward control (FF) is incorporated with the PI-PD controller to enhance the overshoot reduction characteristic in attaining a better transient response, and lastly the disturbance compensator (Kz) is integrated as an additional feedback element to reduce the sensitivity function magnitude for robustness enhancement. The proposed controller - FF PI-PD + Kz has a simple and straightforward design procedure. The usefulness of the proposed controller is evaluated experimentally.

Observer-based feedback for the magnetic levitation system

2011 ◽  
Vol 34 (4) ◽  
pp. 422-435 ◽  
Author(s):  
Jerzy Baranowski ◽  
Paweł Piątek
Keyword(s):  
Magnetic Levitation ◽  
Numerical Differentiation ◽  
Careful Analysis ◽  
High Gain ◽  
Model Parameters ◽  
Stable Operation ◽  
Levitation System ◽  
Non Linear ◽  
Magnetic Levitation System ◽  
The Mathematical Model

Control of active magnetic bearings is an important area of research. The laboratory magnetic levitation system can be interpreted as a model of a single axis of bearings and is a useful testbed for control algorithms. The mathematical model of this system is highly non-linear and requires careful analysis and identification. The system is observable from position measurements as long as the electromagnet is powered as shown during the research. Practically measurable signals are the position and the coil current. The velocity that is necessary for any stabilizing control usually is obtained by numerical differentiation of the position. A more sophisticated approach is to estimate the velocity with an observer. Efficient observer types for this system are high-gain and non-linear reduced observers. The velocity estimated by an observer can be effectively used instead of a derivative in PID control of the position. Such an approach substantially improves control quality and extends the range of system’s stable operation. Even greater improvement is introduced by the addition of the non-linear feedforward to the control structure. The best results, provided the model parameters are correctly identified, are obtained with a control system consisting of the PID controller, the high-gain observer and the non-linear feedforward.

Positioning control of magnetic levitation system by SMC

2005 ◽  
Author(s):  
Jeong-Woo Jeon ◽  
M. Caraiani ◽  
Ki-Chang Lee ◽  
Don-Ha Hwang ◽  
Joo-Hoon Lee ◽  
...  
Keyword(s):  
Magnetic Levitation ◽  
Positioning Control ◽  
Levitation System ◽  
Magnetic Levitation System

MODIFIED-PID CONTROL WITH FEEDFORWARD IMPROVEMENT FOR 1-DEGREE-OF-FREEDOM PNEUMATIC MUSCLE ACTUATED SYSTEM

2017 ◽  
Vol 79 (5-2) ◽  
Author(s):  
Shin-Horng Chong ◽  
Chun-Yuan Chan ◽  
Kaiji Sato ◽  
Vasanthan Sakthivelu ◽  
Ser-Lee Loh
Keyword(s):  
Pid Control ◽  
Nonlinear Function ◽  
Design Procedure ◽  
Deep Understanding ◽  
Settling Time ◽  
Model Parameters ◽  
Nonlinear Properties ◽  
Highly Nonlinear ◽  
Advanced Controls ◽  
Point To Point

attention due to the favorable advantages that PMA has to offer such as inherent compliant safety, compactness, dust-resistant and powerful, especially for rehabilitation application. However, the highly non-linear phenomenon exhibited by PMA poses a challenge in positioning control of the mechanism. Due to the highly nonlinear properties of the PMA system, it is difficult and challengeable to model the system accurately. Many advanced controls have been proposed, however, majority of them requires accurate model parameters for the design and/ or deep understanding of control theory. Therefore, this research aims to highlight a practical and simple control framework capable of providing ameliorated compensation towards the non-linearities in a PMA positioning system. The proposed controller is a combination of a modified PID control incorporated with a model-based feed-forward element. The modified PID control is cascaded with a modeled-nonlinear function and a linearizer that works to compensate the influence of the nonlinearities. The design procedure of the proposed control remains simple and none of the known parameter is required. The proposed controller is verified experimentally using the constructed testbed – 1DOF PMA system; in point-to-point motion that driving in several step heights (5 mm, 10 mm, 20 mm, and 30 mm). At the step height of 30 mm, the proposed control has demonstrated three times smaller of overshoot and the reduction of 39% of settling time as compared with the conventional PID control. Overall, the experimental results show that the proposed controller is capable of demonstrating a satisfactory transient, with better overshoot reduction characteristic and faster settling time; and robust performance under default and in the presence of the change of load, in comparison with the conventional PID control. 

scholarly journals Proportional-Integral-Derivative Gain-Scheduling Control of a Magnetic Levitation System

2017 ◽  
Vol 12 (5) ◽  
pp. 599 ◽  
Author(s):  
Claudia-Adina Bojan-Dragos ◽  
Radu-Emil Precup ◽  
Marius L. Tomescu ◽  
Stefan Preitl ◽  
Oana-Maria Tanasoiu ◽  
...  
Keyword(s):  
Magnetic Levitation ◽  
Design Procedure ◽  
Gain Scheduling ◽  
State Feedback Control ◽  
Proportional Integral Derivative ◽  
Laboratory Equipment ◽  
Proportional Integral ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
Gain Scheduling Control

The paper presents a gain-scheduling control design procedure for classical Proportional-Integral-Derivative controllers (PID-GS-C) for positioning system. The method is applied to a Magnetic Levitation System with Two Electromagnets (MLS2EM) laboratory equipment, which allows several experimental verifications of the proposed solution. The nonlinear model of MLS2EM is linearized at seven operating points. A state feedback control structure is first designed to stabilize the process. PID control and PID-GS-C structures are next designed to ensure zero steady-state control error and bumpless switching between PID controllers for the linearized models. Real-time experimental results are presented for validation. 

scholarly journals Nested Saturation Function Control of a Magnetic Levitation System

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Octavio Gutiérrez-Frías ◽  
Norma Lozada-Castillo ◽  
J. Alejandro Aguirre-Anaya ◽  
Diego A. Flores-Hernández
Keyword(s):  
Magnetic Levitation ◽  
Feedforward Control ◽  
Tracking Error ◽  
Control Technique ◽  
Saturation Control ◽  
Levitation System ◽  
Exponentially Stable ◽  
Magnetic Levitation System ◽  
Error Dynamics ◽  
Beam Mechanism

The trajectory tracking task of a magnetic levitation system connected to a beam mechanism is solved by means of a nested saturation control with a feedforward term. The flatness property of the system allows to use the nested saturation control technique and the feedforward control to stabilize the output tracking error around the equilibrium. The closed-loop error dynamics is proven to be locally exponentially stable. Numerical simulations prove the effectiveness of the proposal.

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