Abstract
This paper presents issues related to the adaptive control of the drive system with an elastic clutch connecting the main motor and the load machine. Firstly, the problems and the main algorithms often implemented for the mentioned object are analyzed. Then, the control concept based on the RNN (recurrent neural network) for the drive system with the flexible coupling is thoroughly described. For this purpose, an adaptive model inspired by the Elman model is selected, which is related to internal feedback in the neural network. The indicated feature improves the processing of dynamic signals. During the design process, for the selection of constant coefficients of the controller, the PSO (particle swarm optimizer) is applied. Moreover, in order to obtain better dynamic properties and improve work in real conditions, one model based on the ADALINE (adaptive linear neuron) is introduced into the structure. Details of the algorithm used for the weights’ adaptation are presented (including stability analysis) to perform the shaft torque signal filtering. The effectiveness of the proposed approach is examined through simulation and experimental studies.
Highlights
Energies 2021, 14, 3389. https://The continuous development of industrial processes’ automation creates demand for precision, speed and higher productivity [1,2]
We presented issues related to the application of the adaptive neural
We presented issues related to the application of the adaptive neural controller for the drive system with an elastic shaft
Summary
The continuous development of industrial processes’ automation creates demand for precision, speed and higher productivity [1,2]. On the basis of an appropriate dataset describing the relationships between the inputs and the outputs of the model, properties of a given neural network can be assigned [35] This can lead to tunable circuits used for control, observation of state variables, signal prediction, measurement of noise removal or data analysis. The second type of these models—the Elman network—usually contains one hidden layer in which the connection from the neuron outputs to the inputs of subsequent nodes is attached [41] In this application, the Elman recurrent neural network is used as the basic structure applied in the speed controller of the electrical drive with compound mechanical part. The simulation and experimental studies show the work of the speed control structure with the recurrent network, and the impact of the additional neural element on drive performance as well as the effectiveness of the proposed approach are analyzed.
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