T-S Fuzzy-Based Optimal Control for Minimally Invasive Robotic Surgery with Input Saturation

A minimally invasive surgery robot is difficult to control when actuator saturation exists. In this paper, a Takagi-Sugeno fuzzy model-based controller is designed for a minimally invasive surgery robot with actuator saturation, which is difficult to control. The contractively invariant ellipsoid theorem is applied for the actuator saturation. The proposed scheme can be derived using the -infinity control theorem and parallel distributed compensation. The result is rebuilt in the form of linear matrix inequalities for easier calculation by computer. Meanwhile, the uniformly ultimately bounded stable and the prescribed -infinity control performance can be guaranteed. The proposed scheme is simulated in a Novint Falcon haptic device system.

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