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Design of the state controller for the two-mass drive system including the dynamic of the torque control loop

Kamiński M., Szabat K.

Poznan University of Technology Academic Journals. Electrical Engineering

2010

No. 61

89-100

In this paper issues related to vibration suppression in the drive system with an elastic joint are presented. The control structure with a state controller is considered. During the design the mathematical model of the torque control loop is taken into consideration. The influence of the neglected dynamics of torque control loop on the drive performance is shown. To provide the information of non-measurable state variables an Extended Kalman Filter is used. The effectiveness of the proposed structure has been examined under simulation and experimental study.

Neural network control with fuzzy logic compensation

Li X. Z., Bajić V. B., Sha D. H., Wang H. Y.

Journal of Applied Computer Science

2000

Vol. 8, nr 2

31-44

This paper presents a new AI based control strategy. A dynamic neural network is used to identify the plant on-line. The control signal is then calculated iteratively according to the responses of a reference model and the identified neural model of the process. A fuzzy logic block with four very simple rules is added to the loop to improve the overall loop properties. This synergetic AI control paradigm is tested via simulation. The results demonstrate that the proposed control strategy provides better disturbance rejection and tracking properties of the control loop than those achieved by an optimally tuned PID controller.