Research On Active Vibration Control Based On Iterative Learning Control Scheme

Recent years have witnessed the effectiveness of the active control on the wind tunnel model vibration control. By acquiring the structure and environment parameters, the active control can greatly reduce the vibration on the model and the supporters caused by the unsteady aerodynamic force which badly influences the experienced data precision.The iterative learning control has been raised as a new control concept. By correcting the current control command using the previous system error data instead of the exact system parameters, iterative learning control can effectively suppress the vibration of the highly periodic system.This study starts with a theoretical model of the algorithm of basic iterative learning control and presents a mathematical development, thus completing the numerical simulation of the algorithm in the MATLAB software.Chapter 3 presents the algorithm of mixed iterative learning control by combining feedforward algorithm and feedback algorithm, by providing the mathematical model and the simulation in the MATLAB. The numerical result shows that the algorithm of mixed iterative learning control can suppress the system vibration effectively.Chapter 4 presents the experimental study. This experiment attaches an actuator to a cantilever, and the stimulator acts as the aerodynamic force. The result demonstrates that the algorithm of mixed iterative learning control can suppress the vibration of the model by 15 %.