Adaptive Resonant-EIDO-Based Optimized Position Precision Control for Magnetic Levitation System

Wang, Junxiao

doi:10.1109/tie.2022.3186348

Cited by 6 publications

(1 citation statement)

References 31 publications

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“…Tools in the industrial field and also transformation have also used magnetic levitation as a solution to make it easier for a system to operate. The definition of magnetic levitation itself is the process of lifting or shifting an object at a certain reference, without any noise, by creating a gravitational repulsive force of the object by using a magnetic field as an antidote [1][2] [3].…”

Section: Introductionmentioning

confidence: 99%

PID Control of Magnetic Levitation (Maglev) System

Seto

Ma’arif

2023

jfsc

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Magnetic levitation is a process of drifting or shifting an object with a certain reference, by creating a repulsive force from the gravity of an object caused by an electromagnetic field without noise. In modern times like today, with the density of community activities, especially those living in urban areas, it is necessary to be able to carry out activities efficiently as well as quickly. Therefore, the reason for many people to be able to find an innovative solution to make it easier for humans to carry out their activities. One of the innovations that can be a solution to the limited space and time is in the development of magnetic levitation technology. The system that will be used in controlling this maglev is to use a PID controller. Using this PID control will be tested with several , , and values with a setpoint of 950. At the initial tunning with the values =2, =0.01, and =2. Then in the second test using the values =3, =0.1, and =0.3. Software testing is also carried out using matlab. The exact PID value for controlling an elevated object can be found by changing the value of the , , and values that can be searched through a matlab software in the PID tunner feature, which can then be seen the PID tunning results by analyzing the graph that will be displayed by the PID tunner.

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Section: Introductionmentioning

confidence: 99%

PID Control of Magnetic Levitation (Maglev) System

Seto

Ma’arif

2023

jfsc

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Adaptive control of an amplified piezoelectric-driven micropositioning stage based on notch filter structure inspiration and neural network online tuning

Wang,

Lai,

Zhu

2024

Smart Mater. Struct.

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Piezoelectric-driven flexure micro/nanopositioning stages often exhibit a low-damping resonance mode, which can easily excite mechanical resonance during high-speed movement, and significantly impact the control system's stability, control bandwidth, and trajectory tracking accuracy. To mitigate the reliance on the precise modeling of stage dynamics inherent in current resonant controllers, an adaptive control method based on a back propagation (BP) neural network was designed to suppress resonance in real-time. First, a piezoelectric-driven flexure micro/nanopositioning stage system was constructed. Next, a feedback controller similar to a notch filter was designed, with bilinear transformation applied based on the system's inherent parameters to determine the initial values. Finally, the designed adaptive control method was tested through trajectory tracking experiments using a triangular wave signal. The experimental results showed that, when tracking the triangular wave signal, the maximum tracking error was reduced by 72.66% compared to proportional-integral (PI) control alone and by 68.66% compared to proportional integral control combined with a traditional notch filter. The tracking results demonstrate a significant improvement in the stage's stability and tracking accuracy.

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