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Information Journal Paper

Title

SPEED CONTROL OF A SERVO HYDRAULIC ACTUATOR, USING ARTIFICIAL NEURAL NETWORKS AND FEEDBACK ERROR LEARNING ALGORITHM

Pages

  21-31

Abstract

 In this article, speed control of a servo hydraulic rotary actuator is investigated, using flexible structure neural network (NN). The applied architecture of NN is a FEEDBACK ERROR LEARNING (FEL), whose underlying learning strategy is based on the inverse dynamics of the system under control. The classic control output was taken as the cost function to be minimized by the NN. A three-layer feed forward NN was applied and a flexible sigmoid activation function was used for the hidden layer nodes. The learning paradigm was online, making use of the back propagation of error with momentum. A simulation was performed and the results obtained indicated the high capability of the flexible NN in learning inverse dynamics in real time in controlling servo hydraulic systems.

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    APA: Copy

    SADATI, S.H., KARIMI MASOULEH, M., & NAJAFI, FARID. (2007). SPEED CONTROL OF A SERVO HYDRAULIC ACTUATOR, USING ARTIFICIAL NEURAL NETWORKS AND FEEDBACK ERROR LEARNING ALGORITHM. AEROSPACE MECHANICS JOURNAL, 3(3), 21-31. SID. https://sid.ir/paper/101735/en

    Vancouver: Copy

    SADATI S.H., KARIMI MASOULEH M., NAJAFI FARID. SPEED CONTROL OF A SERVO HYDRAULIC ACTUATOR, USING ARTIFICIAL NEURAL NETWORKS AND FEEDBACK ERROR LEARNING ALGORITHM. AEROSPACE MECHANICS JOURNAL[Internet]. 2007;3(3):21-31. Available from: https://sid.ir/paper/101735/en

    IEEE: Copy

    S.H. SADATI, M. KARIMI MASOULEH, and FARID NAJAFI, “SPEED CONTROL OF A SERVO HYDRAULIC ACTUATOR, USING ARTIFICIAL NEURAL NETWORKS AND FEEDBACK ERROR LEARNING ALGORITHM,” AEROSPACE MECHANICS JOURNAL, vol. 3, no. 3, pp. 21–31, 2007, [Online]. Available: https://sid.ir/paper/101735/en

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