Adaptive Fuzzy Tracking Control of Flexible-Joint Robots Based on Command Filtering

The precise tracking control problem for n-link flexible-joint (FJ) robotic systems is addressed. A new adaptive fuzzy command filtered control strategy is presented, where fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinearities of FJ robot systems. Compared with existing backstepping-based methods, the proposed scheme can not only overcome the so-called “explosion of complexity” problem, but also reduce filter errors because of the introducing of an error compensation mechanism. Moreover, regardless of the number of fuzzy rules, only one parameter is required to be adjusted on-line, which reduces significantly the computational cost. The proposed scheme can guarantee that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The simulation results of a two-link robot system confirm our theoretical analysis and a comparison study demonstrates the advantages of the design method in comparison with existing results, such as the backstepping method and the dynamic surface control (DSC) method.