基于迭代学习的液压角振动台控制策略研究

Research on Angular Vibration Hydraulic Table Adopting Iteration-learning-control

液压角振动台是十分复杂的非线性系统,应用传统的控制系统设计方法很难满足其控制要求。引入迭代学习控制算法的非线性控制策略,针对控制系统的稳定性以及迭代学习的收敛性,提出复合迭代学习控制算法,并从频域角度给出其收敛性条件。将仿真结果与实验数据进行对比分析,结果表明:系统压力12MPa条件下,采用该方法角振动台内框具有20Hz(峰—峰值0.4°)的正弦响应能力,且其相位滞后不超过10°,幅值误差不大于±10%,验证了此控制策略的有效性。该复合迭代学习控制策略不仅拓宽了系统频带,而且改善了系统输出对期望信号输入的跟踪精度,为液压角振动台的高性能实时控制开辟了新途径。

Angular vibration hydraulic table is a kind of complex and non-linear system. Applying traditional controller to the angular vibration system,it is difficult to increase the control accuracy to a high level. This paper applied a kind of non-linear control strategy which is iteration-learning-control to control angular vibration hydraulic table. Aiming at the stabilization of the control system and the convergence of the iteration-learning-control,a compound iteration-learning-control is adopted,and the convergence criterion is given from the view of frequency-domain. Comparison simulation with experiment,the results show that the inner frame of the angular vibration hydraulic table has the response capability of 20 Hz（0.4°peak to peak value）,the lag of phase is no more than 10°and the error of value is less than ±10% under the pressure of 12 MPa. The results verify the effectiveness of the compound iteration-learning-control strategy,which can increase the bandwidth of the system and improve the precision of the system during tracking the expected input signal. The compound iterative-learning control also provides a new way in high performance real-time control of angle vibration hydraulic table.