Minimum Operator-Based Data-Driven Sliding Mode Control for a Magnetorheological Fluid Dual Clutch
针对磁流变液双离合器建模难、非线性强的问题，提出一种数据驱动离散滑模控制方法，利用实时数据模型和最小算子滑模趋近律，实现变速和牵引工况下的扭矩跟踪控制。
The control of magnetorheological fluid dual clutch (MRFDC) has been challenging due to their modeling challenges, high complexity, strong nonlinearity, and rate-dependent hysteresis, especially in the transient states in which they are supposed to perform gear shifting and traction tracking. Motivated by this, this article presents a data-driven discrete-time sliding mode control (DSMC) approach for the transmission torque control of the magneto-rheological fluid dual clutch (MRFDC). This control method eliminates the model dependence and simplifies the control strategy synthesis by employing a compact form dynamic linearization data model, which is constructed from real-time output torque and input current measurements of the MRFDC. Furthermore, based on the proposed data model, the DSMC is employed based on a minimum operator sliding mode reaching law to deal with the rate-dependent hysteresis and nonlinearity of the MRFDC. Experimental studies validate that the presented control method provides satisfactory torque tracking performance in both transient and steady states.