Exact linearization and fuzzy logic applied to the control of a Magnetic Levitation System

Torres, Luiz H. S.; Vasconcelos, Carlos A. V.; Schnitman, Leizer; Souza, J. A. M. Felippe de

doi:10.1109/fuzzy.2010.5584196

Cited by 6 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, a unitary step reference without disturbances was applied. The initial estimatives for plant parameters were chosen next to their nominal values in (27):…”

Section: Simulation Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Smooth indirect adaptive sliding mode control

Teixeira

Oliveira

Araujo

2013

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this paper, an indirect approach to the dual-mode adaptive robust controller (DMARC) is proposed, which combines the typical transient and robustness properties of variable structure systems with a smooth control signal in steady state, typical of conventional adaptive controllers, as model reference adaptive controller. The aim of this indirect version, here named indirect DMARC, is to provide a more intuitive controller design, based on physical plant parameters, as resistances, inertia moments, capacitances, and so on, maintaining DMARC properties. In this paper, a stability analysis for the proposed controller and simulations to an unstable second-order plant will be presented.

show abstract

“…First, a unitary step reference without disturbances was applied. The initial estimatives for plant parameters were chosen next to their nominal values in (27):…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The main motivation to the development of this work was in the increasing use of IVS-MRAC in practical applications [26][27][28][29][30].…”

mentioning

confidence: 99%

Smooth indirect adaptive sliding mode control

Teixeira

Oliveira

Araujo

2013

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…The functions F(X) and ) (X G that contain the nonlinearities of the system can be set as follows in (13) and (14)…”

Section: Linearization Of the Mlsmentioning

confidence: 99%

Feedback Linearization and Model Reference Adaptive Control of a Magnetic Levitation System

Torres¹,

Schnitman²,

Júnior³

et al. 2012

SIC

Self Cite

View full text Add to dashboard Cite

Abstract:The aim of this paper is to combine two techniques to control a nonlinear Magnetic Levitation System (MLS). Firstly, a feedback linearization technique (here, exact linearization with state feedback) is applied to obtain a linear system. Secondly, the linearization is made via direct cancellation of nonlinear functions, which represent the phenomenological model of the system. Finally, to deal with the presence of uncertainty in the system model, an adaptive controller is used. The controller is based on model reference adaptive control to estimate the functions that contain the nonlinearities of the system. The exact linearization and the adaptive controller were implemented in a simulated environment (Matlab Simulink ©). The linear adaptive controller structure guarantees the parameters adaptation and the overall stability of the system. The results show that the controller output signal tracks a reference input signal with a small error.

show abstract

Feedback linearization based optimal controller design for electromagnetic levitation system

Gandhi

Adhyaru

2016

2016 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT)

View full text Add to dashboard Cite

Exact linearization and fuzzy logic applied to the control of a Magnetic Levitation System

Cited by 6 publications

References 5 publications

Smooth indirect adaptive sliding mode control

Smooth indirect adaptive sliding mode control

Feedback Linearization and Model Reference Adaptive Control of a Magnetic Levitation System

Feedback linearization based optimal controller design for electromagnetic levitation system

Contact Info

Product

Resources

About