模糊增益P型迭代学习控制器的FPGA实现

Fuzzy Gain P-type Iterative Learning Controller Based on FPGA

针对非线性系统模型在P型迭代学习过程中,固定不变的学习增益会使学习系统的收敛速度很慢,鲁棒性差,提出采用模糊推理来整定P型迭代学习增益的方法,即提高了鲁棒性又保证了精度,并利用FPGA完成模糊增益P型迭代学习控制器的设计。通过理论分析和硬件测试验证了该方法的有效性,并且得出该方法的学习速度与学习效果均优于传统学习系统的结论。

In the iterative learning system, the fixed learning gain for nonlinear system model can make convergence rate slow and robustness bad. The method of using fuzzy inference to P-type learning gain tuning is presented which improves the robustness and ensures the accuracy. Fuzzy P-type iterative learning controller design is based on FPGA. Theoretical analysis and hardware test show that the method is effective, the learning speed and learning effect is superior to the traditional learning systems