Rotor multi-frequency vibration active control algorithm for interference vector adaptive identification
A technology of self-adaptive identification and active control, applied in the direction of self-adaptive control, general control system, control/regulation system, etc., can solve problems such as poor control effect
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Embodiment 1
[0057] Introduce the specific content of the present invention in conjunction with an active rotor system, the structural block diagram of the active rotor system is as follows figure 2 As shown, it is mainly composed of controller, actuator, rotor system and displacement sensor. The working principle of the active rotor system is that the displacement sensor detects the rotor displacement of the rotor system, and the rotor displacement detection value x(t) is related to the displacement given value x 0 The difference after comparison is sent to the controller, and the controller sends a control signal u(t) to the actuator, and the actuator generates a control force to act on the rotor system to realize the stable operation of the rotor system. Different types of active rotor systems are mainly different in actuators. For example, for the commonly used electromagnetic bearing-rotor system, the actuators are power amplifiers and electromagnetic bearing bodies.
[0058] The im...
Embodiment 2
[0093] In order to verify the effectiveness of the above interference vector adaptive identification algorithm, the performance of the interference identification and strategy is verified by MATLAB simulation.
[0094] In this embodiment, the actual interference vector is set to d l1 =0.1∠π / 3, angular frequency ω=100πrad / s, step vector amplitude coefficient R s =0.25, Δθ=π / 2.
[0095] Figure 4(a)-Figure 4(b) The simulation results of the identification of the strategy and the interference suppression process under the condition of no noise are given, and the interference suppression strategy is enabled at the simulation time of 0.1s. Figure 4(a) shows the objective function value A before and after starting the algorithm 1 The time domain waveform of , Fig. 4(b) is the interference vector identification result d 1 with actual value d l1 contrast. Figure 4(b) shows that the algorithm has good convergence speed and accurate identification results.
[0096] In the variabl...
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