This article puts forward inductive magnetic suspension spherical active joints and has researched on its mechanism. The expression of motor’s electromagnetic torque is derived from the point of power balance of three-dimensional electromagnetic model, and on the basis of the air gap magnetic flux density distribution, we establish the joint’s mathematical model of electromagnetic levitation force. The relationship between the two of displacement, angle, and current and the transfer function expression of motor system are derived by the state equation and the inverse system theory We established the inverse system of joint’s original system using fuzzy neural network theory and simplified coupling relationship of the motor’s complex multiva...
The dynamic behavior of a magnetorheological (MR) damper is well portrayed using a Bouc-Wen hysteres...
This paper presents, an adaptive finite impulse response (FIR) filter based controller used for the ...
The article is devoted to the application of neural network methods and genetic algorithms in solvin...
Magnetic levitation (Maglev) systems are usually strongly nonlinear, open-loop unstable and fast res...
This report presents a fuzzy modeling and tracking control methodology for an active vibration contr...
Bearingless induction motor is a multi-variable, nonlinear and strong coupling object, the existing ...
Dynamic modeling of magnetic suspension isolator using artificial neural network: a modified genetic...
Magnetic levitation train with high speed, comfort, low energy consumption and low emission is a goo...
Studies on active magnetic bearing (AMB) systems are increasing in popularity and practical applicat...
To control the position of the magnetic levitation ball more accurately, this paper proposes a deep ...
This paper presents a new approach for improving performances of magnetic levitation system. Control...
This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learnin...
AbstractThis paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive...
Abstract — This paper presents a nonlinear servo-control design based on Fuzzy model for safer and ...
To reduce engine vibration, a semi-active controlled magnetorheological suspension is designed. Firs...
The dynamic behavior of a magnetorheological (MR) damper is well portrayed using a Bouc-Wen hysteres...
This paper presents, an adaptive finite impulse response (FIR) filter based controller used for the ...
The article is devoted to the application of neural network methods and genetic algorithms in solvin...
Magnetic levitation (Maglev) systems are usually strongly nonlinear, open-loop unstable and fast res...
This report presents a fuzzy modeling and tracking control methodology for an active vibration contr...
Bearingless induction motor is a multi-variable, nonlinear and strong coupling object, the existing ...
Dynamic modeling of magnetic suspension isolator using artificial neural network: a modified genetic...
Magnetic levitation train with high speed, comfort, low energy consumption and low emission is a goo...
Studies on active magnetic bearing (AMB) systems are increasing in popularity and practical applicat...
To control the position of the magnetic levitation ball more accurately, this paper proposes a deep ...
This paper presents a new approach for improving performances of magnetic levitation system. Control...
This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learnin...
AbstractThis paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive...
Abstract — This paper presents a nonlinear servo-control design based on Fuzzy model for safer and ...
To reduce engine vibration, a semi-active controlled magnetorheological suspension is designed. Firs...
The dynamic behavior of a magnetorheological (MR) damper is well portrayed using a Bouc-Wen hysteres...
This paper presents, an adaptive finite impulse response (FIR) filter based controller used for the ...
The article is devoted to the application of neural network methods and genetic algorithms in solvin...