Adaptive Neural Piecewise Implicit Inverse Controller Design for a Class of Nonlinear Systems Considering Butterfly Hysteresis
针对蝴蝶滞回特性，提出一种自适应神经分段隐式逆控制策略，无需构建解析逆模型即可补偿滞回，在介电弹性体执行器平台上验证了有效性。
In this article, an adaptive neural piecewise implicit inverse control strategy is proposed to effectively compensate for butterfly hysteresis effectively. First, a new butterfly Krasnoselskii–Pokrovskii (BKP) model is developed for the double-loop butterfly hysteresis characteristics. Second, an adaptive neural piecewise implicit inverse control strategy is designed to mitigate the butterfly-like hysteresis without constructing its analytical inverse model. Finally, experimental results on the dielectric elastomer actuator (DEA) motion control platform demonstrate the effectiveness of the adaptive neural piecewise implicit inverse control strategy.