Fuzzy logic-based adaptive control scheme for magnetic levitation systems

2017 ◽  
Author(s):  
Claudia-Adina Bojan-Dragos ◽  
Radu-Emil Precup ◽  
Stefania Hergane ◽  
Teodor-Adrian Teban ◽  
Emil M. Petriu
Keyword(s):  
Fuzzy Logic ◽  
Adaptive Control ◽  
Magnetic Levitation ◽  
Control Scheme ◽  
Adaptive Control Scheme

scholarly journals Enhanced Model Reference Adaptive Control Scheme for Tracking Control of Magnetic Levitation System

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1455
Author(s):  
Rahul Sanmugam Gopi ◽  
Soundarya Srinivasan ◽  
Kavitha Panneerselvam ◽  
Yuvaraja Teekaraman ◽  
Ramya Kuppusamy ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Tracking Control ◽  
Magnetic Levitation ◽  
Model Reference ◽  
Adaptive Scheme ◽  
Control Scheme ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
Model Reference Adaptive ◽  
Adaptive Control Scheme

Magnetic Levitation is a process in which an object is suspended with the support of the magnetic field. Despite being an unstable system, Magnetic Levitation Systems (MAGLEV) have profound applications in various fields of engineering. MAGLEV systems are sensitive, unstable, and nonlinear and uncertainties always pose a challenge in Controller Design. As a solution, adaptive controllers came into existence with adaptation mechanisms to cover the system uncertainties. In this study, a simple, novel, and an effective approach to the Enhanced Adaptive Control scheme is proposed for the ball position control and tracking of an unstable Magnetic Levitation System. The proposed Enhanced Model Reference Adaptive Scheme (EMRAC) follows the same phenomenon of the Model Reference Adaptive Scheme (MRAC) with a slight difference in its control strategy. The proposed scheme consists of Proportional-Integral-Velocity plus Feed Forward as the control structure and a modified version of the standard tuning rule is used as the adaptation mechanism. The control scheme is applied to a standard benchmark Magnetic Levitation System and the tracking performance of the scheme is tested by applying square and multi-sine pattern trajectories to the Magnetic Levitation System. The performance of the developed Enhanced MRAC performance is compared with that of the Proportional Integral Velocity with Feedforward Control (PIV+FF) scheme and the proposed control scheme is proven to be more suitable. The performance of the proposed scheme is also analyzed with Power Spectral Density and Root Mean Square Error to evaluate the ball position tracking control. It is inferred from the experimental results that Enhanced MRAC accommodates the changes and makes the system more reliable with good tracking ability.

Adaptive Control Scheme for Coupled Tank Process

2018 ◽  
pp. 89-95
Author(s):  
Vinodhini M.
Keyword(s):  
Adaptive Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Control Scheme ◽  
Direct Model ◽  
Multivariable Process ◽  
Model Reference Adaptive ◽  
Siso System ◽  
Adaptive Control Scheme

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.

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