Model predictive control of magnetic levitation system

Alkurawy, Lafta E. J.; Mohammed, Khalid G.

doi:10.11591/ijece.v10i6.pp5802-5812

Cited by 2 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In practical applications, as the requirements for fast dynamic response, steady-state accuracy, and anti-interference ability of the system increase, quite a few scholars have proposed various advanced control methods [1]- [5]. The structure of fuzzy control rules is simple, which reduces the complexity of algorithm design and has strong robustness.…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Sliding Mode-Fuzzy PID Control Based on Maglev System

Zhang

2021

IEEE Access

View full text Add to dashboard Cite

The magnetic levitation system is a typical open-loop unstable system. To weaken the chattering phenomenon of sliding mode control (SMC), a hybrid control strategy of particle swarm sliding mode-fuzzy PID control was designed. This strategy uses particle swarm optimization (PSO) to optimize the SMC using the method of exponential approach law, so as to obtain the best sliding mode surface parameters and exponential approach rate coefficients, thus shortening the time required to approach the stable region when the nonlinear system is far from the stable point; a state supervision controller was designed by analyzing the stable conditions of sliding mode. When the system approaches the stable region, it smoothly transitions to fuzzy PID control, thereby weakening the chattering phenomenon of SMC. To verify the dynamic performance of the designed algorithm, a magnetic levitation ball system was selected as the controlled object. Through simulation and experiment, it was verified that the controller had strong robustness and strong anti-interference performance. It effectively weakened the chattering and had good adaptability to external disturbance and state variable crossing.

show abstract

Section: Introductionmentioning

confidence: 99%

Particle Swarm Sliding Mode-Fuzzy PID Control Based on Maglev System

Zhang

2021

IEEE Access

View full text Add to dashboard Cite

show abstract

Application of PID and self-tuning fuzzy PID control methods in the control of non-linear magnetic levitation system

Karabacak

2024

JIENS

View full text Add to dashboard Cite

Because of the Magnetic Levitation System's (MLS) low energy consumption and little friction two factors that are deemed crucial for unstable and nonlinear systems MLS research is now being conducted in the engineering area. This article discusses the comparison of the performance of control theories used by applying advanced control theories to cope with the complexity of the structure and controllability difficulties of MLS. The control methods compared are Proportional–Integral–Derivative (PID) and Self-Tuning Fuzzy PID (STFPID) methods. These methods were developed in the MATLAB environment. The MLS model created in the MATLAB environment was subjected to the suggested control methods, and the outcomes were compared. The outcomes unequivocally demonstrate that MLS location control may make use of PID and STFPID techniques. Four criteria were used to compare the developed control approaches performances. These are the criteria; rise time, settling time, percent maximum overshoot and overshoot value. It is clearly seen in the results that the STFPID control method provides control of the MLS with greater stability than the PID control method.

show abstract

Model predictive control of magnetic levitation system

Cited by 2 publications

References 26 publications

Particle Swarm Sliding Mode-Fuzzy PID Control Based on Maglev System

Particle Swarm Sliding Mode-Fuzzy PID Control Based on Maglev System

Application of PID and self-tuning fuzzy PID control methods in the control of non-linear magnetic levitation system

Contact Info

Product

Resources

About