PID Control of Multisources Complex Excitations Active Vibration Isolation System: An Improved Particle Swarm Optimization Algorithm

Abstract

Active vibration isolation technology is the key technique to solve the vibration isolation problems related to the multisources complex excitations vibration isolation system. The electromagnetic actuators-based multisources complex excitations active vibration isolation system is built. Additionally, in view of the complex structure and strong coupling of the system, the least-squares method to identify and obtain the mathematical model of the vibration isolation system is adopted. Furthermore, this paper also sets up the acceleration feedback-based PID control model for multisources complex excitations active vibration isolation system, proposes an improved particle swarm optimization (PSO) algorithm of dynamic inertia weight factors used to optimize parameters of the built PID control model, and conducts simulation analysis. The simulation results show that, compared with the passive system before the control, the multisources complex excitations active vibration isolation system under the PID control has the far less peak-to-peak amplitude of acceleration which is transmitted to the foundation and has the much better vibration isolation effect. Finally, the paper conducts experimental verification, which demonstrates that active vibration control effect is identical to the simulation results and the vibration control effect is significantly improved.

A Comparative Study Based on Different Control Algorithms for Suppressing Multistage Gear Transmission System Vibrations

“…And the D control has an important effect on increasing the stability of the system and suppressing the overshoot. Thus, determining the three parameters of P, I, and D is the main mission for designing the PID controller [22]. The block Figure 6(a), and the output of PID controller in time domain is given as below:…”

Active vibration control using nonlinear auto-regressive neural network to identify secondary channel

“…The effective vibration isolation band of passive noise control (PNC) method is generally high, while the low-frequency vibration noise makes the passive vibration isolation method poor in suppressing low-frequency disturbances due to the low-frequency band range. 1,2 Active noise control (ANC) methods can effectively suppress low-frequency periodic disturbances, 3,4 but feedback control methods such as PID algorithm and fuzzy control algorithm are difficult to compensate the phase lag and amplitude decay caused by the secondary channels in the active vibration control system, [5][6][7][8] and the parameters tuning also depends on empirical methods, so the application is more difficult and the vibration damping effect is limited. The adaptive feedforward control algorithm is based on the idea of feedforward control, and the adaptive algorithm is used for self-tuning the controller parameters according to the model of the identified secondary channels so that theoretically the best controller can be obtained to compensate and improve the dynamic characteristics of the secondary channels, and thus a good vibration damping effect can be achieved for the low-frequency periodic disturbances.…”