Input–output feedback linearizing control of linear induction motor taking into consideration the end-effects. Part I: Theoretical analysis

Alonge, F.; Cirrincione, Maurizio; Pucci, Marcello; Sferlazza, Antonino

doi:10.1016/j.conengprac.2014.08.009

Cited by 33 publications

(30 citation statements)

References 16 publications

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“…The simulation and experimental results indicated that this approach was capable of decoupling control and exhibited good performance. Alonge [14] introduced the theoretical formulation of the IOFL control technique applied to linear IMs. The theory described the control design criteria by considering the constraints on the control and controlled variables that arose from applying this control technique in a real scenario.…”

Section: State Of the Artmentioning

confidence: 99%

Nonlinear Differential Geometry Method and Its Application in Induction Motor Decoupling Control

Fan¹,

Zhong²

2016

JESTR

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An alternating current induction motor is a nonlinear, multi-variable, and strong-coupled system that is difficult to control. To address this problem, a novel control strategy based on nonlinear differential geometry theory was proposed. First, a five-order affine mathematical model for an alternating current induction motor was provided. Then, the feedback linearization method was used to realize decoupling and full linearization of the system model. Moreover, a general and simplified control law was adopted to facilitate practical applications. Finally, a controller was designed using the pole assignment method. Simulation results show that the proposed method can decouple the system model into two independent subsystems, and that the closed-loop system exhibits good dynamic and static performances. The proposed decoupling control method is useful to reduce the system complexity of an induction motor and to improve its control performance, thereby providing a new and feasible dynamic decoupling control for an alternating current induction motor.

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Section: State Of the Artmentioning

confidence: 99%

Nonlinear Differential Geometry Method and Its Application in Induction Motor Decoupling Control

Fan¹,

Zhong²

2016

JESTR

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“…Choi and Ahn [15] experimentally implemented a feedback linearisation based controller for successful position and attitude control of a quadcopter. Alonge et al [16] presented the theoretical development of a feedback linearisation based controller for the control of linear induction motor (LIM) drives with dynamic end effects which give rise to significant nonlinear behaviour. These results were later validated through experimental tests [17], which showed significant improvements when feedback linearisation was applied adaptively.…”

Section: Introductionmentioning

confidence: 99%

Experimental feedback linearisation of a non-smooth nonlinear system by the method of receptances

Lisitano

Jiffri

Bonisoli

et al. 2018

Mathematics and Mechanics of Solids

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Input-output partial feedback linearisation is experimentally implemented on a non-smooth nonlinear system without the necessity of a conventional system matrix model for the first time. The experimental rig consists of three lumped masses connected and supported by springs with low damping. The input and output are at the first degree of freedom with a non-smooth clearance-type nonlinearity at the third degree of freedom. Feedback linearisation has the effect of separating the system into two parts: one linear and controllable and the other nonlinear and uncontrollable. When control is applied to the former, the latter must be shown to be stable if the complete system is to be stable with the desired dynamic behaviour.

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“…Multivariable feedback control, derived from the system's inputoutput relationship, has been considered one of the efficient model-based control solutions to deal with multivariable non-linear systems [5]. It has been applied to the IM for variable speed operation and achieved significant improvement compared to the field oriented control (FOC), widely used for IM control [6][7][8][9]. However, this method is heavily dependent on the system states and parameters as it is developed from the machine state-model, where the quantities of rotor speed, rotor flux and stator current are required in the implementation of this controller.…”

Section: Introductionmentioning

confidence: 99%

Torque and state estimation for real‐time implementation of multivariable control in sensorless induction motor drives

Merabet¹,

Tanvir²,

Beddek³

2017

IET Electric Power Applications

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This study presents a strategy for estimating the states and the load torque to implement a feedback linearisation controller for induction motor drives. The multivariable control is carried out using input-output linearisation feedback law in order to track profiles of the rotational speed and the rotor flux amplitude. The unknown load torque is compensated by an estimator based on the speed error. The state estimation requires only the measurements of the stator voltagescurrents. The estimation method is not invasive as no mechanical sensors are needed. Experimental platform equipped with sensors at the load side, for measuring the speed and the torque of the motor driven by the Opal-RT real-time system, was implemented to verify the accuracy of the proposed estimation method to implement the multivariable control.

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Input–output feedback linearizing control of linear induction motor taking into consideration the end-effects. Part I: Theoretical analysis

Cited by 33 publications

References 16 publications

Nonlinear Differential Geometry Method and Its Application in Induction Motor Decoupling Control

Nonlinear Differential Geometry Method and Its Application in Induction Motor Decoupling Control

Experimental feedback linearisation of a non-smooth nonlinear system by the method of receptances

Torque and state estimation for real‐time implementation of multivariable control in sensorless induction motor drives

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