Minimum Operator-Based Data-Driven Sliding Mode Control for a Magnetorheological Fluid Dual Clutch
Mingdong Hou, Jin Zhao, Jie Tian, Haiping Du
Abstract
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.