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The paper deals with the application of neural networks for state variables estimation of the electrical drive system with an elastic joint. The torsional vibration suppression of such drive system is achieved by the application of a special control structure with a state-space controller and additional feedbacks from mechanical state variables. Signals of the torsional torque and the load-machine...
This paper presents a modified sliding-mode structure implemented for the speed control of a two-mass drive. A characteristic feature of the presented control method is the higher rank of the switching function caused by the application of an integral element (sliding mode with an integral function control). The proposed control system is a combination of a sliding-mode controller and a linear controller...
The paper deals with the application of the feed-forward and cascade-forward neural networks to mechanical state variable estimation of the drive system with elastic coupling. The learning procedure of neural estimators is described and the influence of the input vector size and neural network structure to the accuracy of state variable estimation is investigated. The quality of state estimation by...
In the paper a robust control system with the fuzzy adaptive controller and the additional compensator is presented. A model reference adaptive control system (MRAC) is applied to a drive system with changeable parameters. The speed controller is based on the neuro-fuzzy network. The additional compensator relaying on the sliding-mode theory is used to improve the dynamical characteristics of the...
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