Second-Order Nonlinear Trajectory Smoother for Position Control of Linear Switched Reluctance Motor

Wang, J.; Tsang, K.M.; Cheung, N.C.

doi:10.1080/02286203.2006.11442363

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…However, the proposed controller ignores the influence of time-varying parameters and disturbances. Wang et al [22] proposed a second-order trajectory smoothing filter tracking control strategy by combining feedforward and linear feedback control. This method effectively improves the buffeting of the system and simplifies the controller solution.…”

Section: State Of the Artmentioning

confidence: 99%

Optimization of Linear Switched Reluctance Motor for Single Neuron Adaptive Position Tracking Control based on Fruit Fly Optimization Algorithm

Xu¹,

Tang²,

Yang³

et al. 2020

JESTR

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A linear switched reluctance motor (LSRM) drive system is a complex and strongly coupled nonlinear system with time-varying parameters, friction and external disturbances. An intelligent position tracking control based on fruit fly optimization algorithm (FOA) was proposed in this study to effectively solve the effects of parameter uncertainty, load disturbance, thrust fluctuation, and friction on the performance of the LSRM system. A mathematical model of LSRM was constructed on the basis of its structure and characteristics, and spatial discretization was conducted. A single neuron adaptive controller was designed for the discretized LSRM, and its parameters were adjusted and optimized online using the FOA. The accuracy of the model was verified through experiments. Results show that the propose controller has high tracking (rotor position steady-state error is less than 10%) and strong anti-interference performance (restores to the desired rotor position instruction in 0.01 s). The proposed controller can better track the rotor position when the rotor position instruction changes, with smaller overshoot (less than 10%) and can control the PID up to 30% compared with proportional-integral-derivative (PID) controllers. The proposed method has high position tracking accuracy and strong robustness to external disturbances.

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Section: State Of the Artmentioning

confidence: 99%

Optimization of Linear Switched Reluctance Motor for Single Neuron Adaptive Position Tracking Control based on Fruit Fly Optimization Algorithm

Xu¹,

Tang²,

Yang³

et al. 2020

JESTR

View full text Add to dashboard Cite

show abstract

Electrical drive system for switched reluctance motor

Aljaism

Nagrial

Rizk

2008

2008 Second International Conference on Electrical Engineering

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High Performance Linear Actuation Systems

Cheung

2006

2006 2nd International Conference on Power Electronics Systems and Applications

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To achieve high precision linear movements, most actuators use a standard rotary motor and couple it to a mechanical rotary to linear translator. However, this is not the most optimum method. For high precision and high speed linear motions, this paper proposes to use dedicated direct-drive linear actuator with intelligent controller to accomplish the job. This type of implementation has the advantages of simple mechanism, easy maintenance, and low operation cost. This paper will explore several types of linear drives, including Permanent Magnet Synchronous Linear Motor, and Linear Switched Reluctance Motor.

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Second-Order Nonlinear Trajectory Smoother for Position Control of Linear Switched Reluctance Motor

Cited by 3 publications

References 10 publications

Optimization of Linear Switched Reluctance Motor for Single Neuron Adaptive Position Tracking Control based on Fruit Fly Optimization Algorithm

Optimization of Linear Switched Reluctance Motor for Single Neuron Adaptive Position Tracking Control based on Fruit Fly Optimization Algorithm

Electrical drive system for switched reluctance motor

High Performance Linear Actuation Systems

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