On-line gain-tuning IP controller using real-coded genetic algorithm

Lin, Faa Jeng; Shieh, Hsin Jang; Shyu, Kuo-Kai; Huang, Po-Kai

doi:10.1016/j.epsr.2004.03.013

Cited by 38 publications

(26 citation statements)

References 21 publications

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“…The stator and rotor voltage equations of the LIM in the synchronously rotating reference frame are described through the modification of the traditional rotary induction motor as follows [4]: …”

Section: Figure 1 Configuration Of a Limmentioning

confidence: 99%

“…Along with this issue, a high performance and robust position controller design in linear motion system has been an important topic. Recently, several works have been studied to control the position of a linear induction motor (LIM) as a single unit without considering the APS [3][4]. However, the scheme in [4] is too complex to apply in the physical APS.…”

mentioning

confidence: 99%

“…Recently, several works have been studied to control the position of a linear induction motor (LIM) as a single unit without considering the APS [3][4]. However, the scheme in [4] is too complex to apply in the physical APS. Even though the compensation methods using a model reference adaptive control or the load torque observer have been developed to improve the control performance [5][6], they work well only when the variation of an unknown disturbance is not large during sampling interval.…”

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confidence: 99%

See 2 more Smart Citations

A DSP-based Robust Position Controller of a Single-sided Linear Induction Motor for Automatic Picking System

Choi¹,

Kim²,

Yoo³

et al. 2014

IJCA

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Section: Figure 1 Configuration Of a Limmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

A DSP-based Robust Position Controller of a Single-sided Linear Induction Motor for Automatic Picking System

Choi¹,

Kim²,

Yoo³

et al. 2014

IJCA

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show abstract

“…For example, if any sudden or unexpected change in motor speed or load disturbance occurs, that results to an undesired overshoot in motor speed, long settling time, high stator flux and torque ripples. In the literature survey, lots of control strategies has been proposed to tune the gain values of PISC, like Ziegler-Nichols, root locus, pole assignment design and etc [4]. Therefore, on-line tuning based speed controller is in demand to get high performance drive.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic and Sliding-Mode Speed Control Based Direct Torque and Flux Control Scheme to Improve the Performance of an Induction Motor Drive

Ramesh¹,

Panda²,

Kumar³

2014

ijeei

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Abstract:In this research study, the performance of direct torque and flux control (DTFC) induction motor drive (IMD) is presented using four different speed control techniques. The performance of IMD mainly depends on the design of speed controller. The PI speed controller (PISC) requires precise mathematical model, continuous and appropriate gain values. Therefore, adaptive control based speed controller is desirable to achieve high performance drive. The sliding-mode speed controller (SMSC) is developed to achieve continuous control of motor speed and torque. Furthermore, the fuzzy logic speed controller (FLSC) and fuzzy sliding-mode speed controller (FSMSC) is designed to obtain high performance, dynamic tracking behavior, speed accuracy and also robustness to parameter variations. The performance of each control technique has been tested for its robustness to parameter uncertainties and load disturbances. The detailed comparison of different control schemes are carried out in a MATALB/Simulink environment at different speed operating conditions, such as, forward and reversal motoring under no-load, load and sudden change in speed.Keywords: Direct torque control, induction motor drive, fuzzy logic speed controller, sliding mode speed controller, fuzzy sliding mode speed controller. IntroductionIn recent times, the adjustable speed drives (ASDs) with induction motor drives (IMDs) are making significant inroads because of robustness, high performance, and rugged structure and widely used in industrial applications such as; electric and hybrid vehicles, traction locomotives, electric propulsion ships The scalar control schemes are simple to implement and gives good steady state response, but poor in dynamic response. However, the vector control method gives good steady state as well as transient response [1]. In the vector control scheme, one of the most popular control method of induction motor drive is known as field oriented control (FOC). It controls an induction motor drive like a separately excited DC motor and it was proposed by F. Blaschke (Direct FOC) and Hasse (Indirect FOC) in early 1970"s [2]. The FOC method has an attractive features but it suffers with some drawbacks, such as; requirement of co-ordinate transformations, current controllers, sensitive to parameter variations. The drawbacks of FOC schemes are minimized with the new control strategy i.e., direct torque control (DTC) scheme, which is proposed by Isao Takahashi and Toshihiko Noguchi, in the mid 1980"s [3].The performance of IMD mainly depends on the design of speed controller. The PISC is widely used in industrial applications as it has a simple structure and offers a good satisfactory performance over a wide range of normal operation. But, the PISC scheme may not give satisfactory performance under load disturbances and it requires precise mathematical model, continuous tuning and accurate gain values of proportional (Kp) and integral (K I ) to achieve high performance drive. It is quite difficult to gain high performance of an IMD us...

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“…Current research works focus on wide speed ranges, especially very low speed ranges [15], or inaccuracy and IM parameter variations [16]. Intelligent techniques such as neural networks, fuzzy control, and genetic algorithms have been utilized to handle the nonlinearities and uncertainties of the IM parameters [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

MOPSO-based predictive control strategy for efficient operation of sensorless vector-controlled fuel cell electric vehicle induction motor drives

El-Gammal¹,

El-Naggar²

2017

Turk J Elec Eng & Comp Sci

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This paper introduces an optimal control strategy of model-based predictive control (MPC) based on multiobjective particle swarm optimization (MOPSO) for a sensorless vector control induction motor, which is used in a fuel cell electric vehicle drive system. The proposed MPC-MOPSO algorithm is implemented to tune the weighting parameters of the MPC controller to tackle all the conflicting objective functions. The paper handles the following fitness functions: minimizing the speed error, minimizing the torque ripple, minimizing the DC-link voltage ripple, and minimizing machine flux ripple. Computer simulations studies have been completed utilizing MATLAB/Simulink with a specific end goal of assessing the dynamic performance of the proposed MPC-MOPSO optimal controller and comparing it with single-objective particle swarm optimization and traditional PI controllers. The simulation results demonstrate the good dynamic response of the proposed MPC-MOPSO optimal tuning strategy over the traditional PI controllers for more accurate tracking performance through the whole speed range, especially at starting conditions and load change disturbances.

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On-line gain-tuning IP controller using real-coded genetic algorithm

Cited by 38 publications

References 21 publications

A DSP-based Robust Position Controller of a Single-sided Linear Induction Motor for Automatic Picking System

A DSP-based Robust Position Controller of a Single-sided Linear Induction Motor for Automatic Picking System

Fuzzy Logic and Sliding-Mode Speed Control Based Direct Torque and Flux Control Scheme to Improve the Performance of an Induction Motor Drive

MOPSO-based predictive control strategy for efficient operation of sensorless vector-controlled fuel cell electric vehicle induction motor drives

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