Adaptive control based on IF–THEN rules for grasping force regulation with unknown contact mechanism

• Design the control scheme for an industrial gripping application with unknown contact mechanism.
• Devise a time varying learning rate for gradient reach with the proof of stability analysis.
• Conduct the experimental system with an industrial parallel grip SCHUNK-WSG 50 validates the performance of the proposed controller.

An industrial gripping application with unknown contact mechanism is considered as a class of unknown nonlinear discrete-time systems. The control scheme is developed by an adaptive network called multi-input fuzzy rules emulated network (MiFREN) within discrete-time domain. The network structure is directly constructed regarding to IF–THEN rules related to gripper and contact mechanism properties. All adjustable parameters require only the on-line learning phase to improve the closed loop performance. The time varying learning rate is devised for gradient reach with the proof of stability analysis. Furthermore, the estimated sensitivity of system dynamic is directly considered within the parameter adaptation. The experimental system with an industrial parallel grip model WSG-50 validates the performance of the proposed controller.