Adaptive Fuzzy Backstepping Control for Stable Nonlinear Bilateral Teleoperation Manipulators With Enhanced Transparency Performance

Abstract

Bilateral teleoperation technology has been widely concerned by its unique advantages in human-machine interaction-based cooperative operation systems. Communication delay, various nonlinearities, and uncertainties in teleoperation system are the main challenging issues to achieve system stability and good transparency performance. In this paper, a globally stable adaptive fuzzy backstepping control design is proposed for nonlinear bilateral teleoperation manipulators to handle the aforementioned issues. For the communication channel, instead of direct transmission of environmental torque signals, the fuzzy-based nonpower approximate environmental parameters are transmitted to the master side for environmental torque prediction, which effectively avoids the transmission of power signals in the delayed communication channel and solves the passivity problem in the traditional teleoperation system. A trajectory generator is implemented in the master side and a trajectory smoothing is applied in the slave side. Subsequently, nonlinear adaptive fuzzy backstepping controllers for master and slave are separately designed to handle the nonlinearities and uncertainties. Theoretically, the great transparency performance of both position tracking and force feedback can be achieved, and the global stability is still guaranteed under communication delay. Comparative experiments are conducted on the real platform, which verify the effectiveness and advantages of the proposed control design in some typical working scenarios.