Acceleration amplitude and phase controller based on the FEL applied to hydraulic vibration generator system

For the two test items of hydraulic vibration generator system, acceleration sinusoidal signal waveform replication, acceleration sweep, Feedback-Error-Learning(FEL) control strategy is utilized to solve the weakness of tracking accuracy and robustness which traditional three variable control strategy can't do. Feedforward neural networks of FEL control strategy was designed, using ADALINE neural networks, normalized LMS, plus characteristics of sinusoidal function. For sinusoidal and sweep reference input, even in cases that valve-controlled cylinder system parameters changed, the designed controller still achieved high tracking accuracy in amplitude and in phase. Furthermore, it has the advantage of simple construct and smaller amount of computation, which can satisfy the demand of control system that requires higher real-time capability and DSPs solution.