符号型自适应模糊控制器

伸缩因子设计是变论域模糊控制的关键, 也是设计的难点. 借助于Lyapunov综合分析方法, 提出一种符号型自适应模糊控制方案, 避免花费精力设计伸缩因子. 方案中使用符号函数替代输入的伸缩运算, 后件调整仍使用积分调节因子. 因此, 本质上它仍是一种论域可变的模糊控制. 相比较变论域模糊控制, 该方案所需规则少, 稳态精度高, 鲁棒性好. Lyapunov稳定性理论保证了跟踪误差的渐近收敛. 最后, 实例证实了方案的可行性.

Symbol-type adaptive fuzzy controller

The design of contraction-expansion factor is crucial in variable universe fuzzy control. Using Lyapunov synthetic analysis, we propose an adaptive fuzzy control with sign function to avoid the design of contraction-expansion factor. In this scheme, the stretch operator of control input employs the sign function instead of the exponential function or the scale function employed in variable universe fuzzy control design, and the consequence adjustment still uses an integral regulation. Compared with the variable universe fuzzy control, the proposed scheme is essentially a kind of fuzzy control with variable universe with less fuzzy rules, higher steady precision and higher robustness to external disturbance. Lyapunov stability theory guarantees the asymptotic convergence of tracking error. A simulation example shows the efficacy of the proposed scheme.