Practical Finite-Time Observer-Based Adaptive Backstepping Super-Twisting Sliding Mode Control for Deep-Sea Hydraulic Manipulator
Gang Chen, Wei Wu, Chenguang Yang, Huosheng Hu, Jingjing Zhang, Jianwei Shi, Chuanyu Wu, Chuanyu Wu
Abstract
Parameter uncertainties and unknown disturbances always exist in the trajectory tracking control of a deep-sea hydraulic manipulators (DHMs), significantly reducing tracking accuracy. To address these issues, a practical finite-time observer-based adaptive backstepping super-twisting sliding mode control method (PFTO-ABSTC) is proposed for precise DHM tracking control. First, a projection-type adaptive law is constructed to handle the parameter uncertainties. In addition, Levant’s Differentiator is employed to obtain velocity of the DHM and construct the adaptive law regression vector, minimizing system noise from differentiation and filtering operations. Second, a practical finite-time observer (PFTO) strategy is proposed to estimates lump disturbances and compensates them in the controller, avoiding high-gain phenomenon of the controller effectively. Then, the PFTO-ABSTC controller is proposed by integrating the backstepping technique, which chattering-free property can be achieved. In addition, the uncertainties and disturbances of the DHM dynamics are well addressed in the closed-loop system, and asymptotic tracking performance can be guaranteed by Lyapunov theory. Finally, comparative experimental results validate the effectiveness of the proposed control strategy. Experimental results show that the proposed method can achieve smaller control errors and better control performance than the ESO-ABSTC, ABSTC, and PID control methods, and the maximum control errors are improved by at least 41.30%, 50.76%, and 66.67%, respectively.