Fuzzy Optimization of Adaptive Integral Terminal Sliding Mode Control for Mechanical Systems With Uncertainties and Disturbances

The robustness of mechanical systems is affected by uncertainties, external disturbances, and chattering. Therefore, a flexible adaptive nonsingular recursive terminal sliding mode control (SMC) is proposed. The advantages are that the constraint error converges to zero within a finite time, the control gain can be adjusted and the chattering is suppressed. The leakage type avoids excessive compensation. Then, fuzzy set theory is introduced to describe uncertainties. A fuzzy set-based optimization strategy is proposed. The impact of control parameters on performance and cost is clearly quantified by optimization algorithms. The best system performance and reasonable control cost are achieved. Finally, the proposed method is validated by a human–machine system as an example. The experiment results show that the average error of the five optimal parameters under the proposed method is 50.44%, 43.02%, and 77.03% of the error under the high-order robust control, the proportional derivative-based robust control, and the fast nonsingular terminal SMC, respectively. Correspondingly, the average control torque is 95.90%, 97.67%, and 99.38% of their, respectively. It can be concluded that the proposed optimal control method can improve the robustness of uncertain systems within the lower control cost.