Ant colony optimization reduced order fuzzy controller

An ant colony optimization algorithm, motor controller technology, applied in observer control, torque ripple control, single motor speed/torque control, etc., can solve the complex control law of fuzzy controller, genetic algorithm convergence and dynamic control The effect is not ideal, etc.

Inactive Publication Date: 2014-02-05
TIANJIN POLYTECHNIC UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

However, the convergence and dynamic control effects of genetic algorithm optimization are not ideal, and the traditional fuzzy controller control law is relatively complicated.

Method used

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  • Ant colony optimization reduced order fuzzy controller
  • Ant colony optimization reduced order fuzzy controller
  • Ant colony optimization reduced order fuzzy controller

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Experimental program
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Embodiment Construction

[0021] figure 1 It is the basic schematic diagram of double closed-loop control of the motor, in which the speed loop can adopt the reduced-order fuzzy controller of the present invention. As shown in the figure, the speed error e and the speed change error pass through the corresponding fuzzy scale factor K e and K ec Change to a fuzzy input variable, through the ant colony algorithm with a forgetting factor of 0.9 and a transfer factor of 0.55, the size range of the fuzzy variable is determined as NB (negative), N (negative), Z (zero), P (positive), PB (Zhengda) five, and its membership distribution function is as follows figure 2 As shown, the number of rules is only 22, such as image 3 shown. Figure 4 for figure 1 The middle drive module, that is, the basic schematic diagram of the motor drive, Figure 5 Hysteretic control is given when Figure 4 The relationship between the drive sequence of the power tubes and the current. Figure 6 In order to improve the ant...

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Abstract

The invention belongs to the field of intelligent control application and relates to reduced order fuzzy intelligent motor controllers, in particular to a reduced order fuzzy motor controller based on the ant colony optimization. The controller comprises an inner closed loop and an outer closed loop. The inner closed loop is a current hysteresis controller body and the outer closed loop is a fuzzy controller body. The reduced order fuzzy motor controller is characterized in that a velocity error and a velocity change error are adopted by the fuzzy control strategy and serve as input, fuzzy output serves as input of a current loop after an ambiguity solving change factor Ku acts on the fuzzy output, the number of fuzzy rules which are optimized through the ant colony optimization is 22, load torque estimation can be conducted by the current hysteresis controller body through observation of change of rotational inertia and a viscous friction coefficient, so that compensation control over a current is achieved, the effect that the torque ripple is restrained is achieved, the control strategy is achieved through a TMS320LF2407A chip, parameters of the chip can be corrected online, and the overvoltage and overcurrent protection functions can be achieved.

Description

technical field [0001] The invention belongs to the application field of intelligent control, and in particular relates to a reduced-order fuzzy intelligent motor controller. Background technique [0002] Brushless DC motors have the advantages of large torque, high efficiency, and no commutation sparks, so they are widely used in industrial servo drives such as aerospace, electric vehicles, and robots. However, in the control of brushless DC motors, there are still many uncertainties, including load changes, friction coefficients, and changes in internal parameters such as motor resistance and inductance. Therefore, further research is needed to suppress its torque fluctuations. At present, some advanced control strategies and new methods of motor structure design are gradually being used to overcome the torque fluctuation of this type of motor, including neural network control, genetic algorithm optimization of controller parameters, fuzzy control, etc. However, the conve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02P6/10H02P6/06H02P23/12
Inventor 肖朝霞赵倩宇
Owner TIANJIN POLYTECHNIC UNIV
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