Control Strategy Of Hydraulically Driven 6-DOF Vibration Test System

Upon the background of National Defense 863 Project to develop 3 axis 6 DOF (degree-of-freedom) hydraulic vibration test system, which is developed by IEST (Institute of Electro-hydraulic Servo Simulation & Test System), the control strategy of the vibration test system has been theoretically and experimentally studied.The control system of 6 DOF vibration table consists of servo control system and vibration control system. The servo control system is used to realize the DOF control mode, i.e., to convert the DOF drive signals to single actuator drive signals. There have large deviations between response signals and input signals with the only servo control system. So the vibration control system is added in the outer control loop of the servo control system. Based on the FRF (frequency response function) of the system, the drive signals are corrected so that the response signals can replicate the expect signals in high degree of accuracy.The servo control system of vibration table consists of DOF composition and decomposition controller, three variable controller and force balance controller. Based on the analysis of 6 DOF matrix control method, 8 DOF matrix control method is presented in this dissertation. Two torsion DOF control loop are added to the original 6 DOF control loop. As the existence of no uniqueness solutions of actuator drive signals in the 6 DOF control mode, the inner forces among actuators vary within wide limits. In 8 DOF control mode, the solutions of actuator drive signals are uniqueness, so the inner forces among actuators are almost constant. The const inner forces are favorable to improve the control precision. Then, the conventional force balance controller is improved. The number of adjustable parameters is reduced to two. The two parameters are independent and can be adjusted individually. At last, experimental results validated the 8 DOF matrix control method and the improved force balance controller.The DOF composition and decomposition matrixes in classical servo control system are got based on the assumption of linearization near the zero position. The matrixes are invariant. This indicates that the conventional matrix control method is inaccurate. Kinematics analysis and the pose control structure of 6 DOF vibration table are presented in this dissertation. Forward solution and jacobian matrix replace the DOF composition and decomposition matrixes in the conventional servo control system. Simulation and experimental results show that the pose control structure based on the kinematics analysis of 6 DOF vibration table is favorable to improve the performance indices of acceleration evenness degree and transverse components in the low-frequency band.FRF H1 estimator is used in the classical 6 DOF waveform replication algorithm to estimate the FRF of the system. It's well known that the H1 estimator is influenced by the noise in the input signals and generates an under-estimation of the true FRF. This paper presents the FRF estimator based on the EV model to reduce the bias error of FRF H1 estimator. The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation. Based on the features of MIMO waveform replication control system, the estimator is simplified. The results of simulation and experiment show that the waveform replication algorithm with the FRF estimator based on the EV model can improve further the control precision.In order to improve the control precision of random vibration PSD replication, the correction algorithm of drive signals PSD and the generation of time domain drive signals are improved in the classical algorithm. First, the drive signals PSD iteration algorithm with different step length in different frequency band is presented to raise the rate of convergence. Second, the method of generating the drive signal in time domain by filtering a series of independent white noise with designed FIR filter is presented. The FIR filter is designed by the Parks-McClellan algorithm with the information contained in the in the drive signal PSD. Due to avoiding the time domain randomization procedure, the execution time of the algorithm is reduced. The results of simulation and experiment show that the improved PSD iteration algorithm is favorable to improve the control precision.