Command Filter-Based Finite-Time Constraint Control for Flexible Joint Robots Stochastic System With Unknown Dead Zones
Yuanbao Dong, Hak‐Keung Lam, Jiapeng Liu, Jinpeng Yu
Abstract
This article studies the problem of finite-time (FT) adaptive constraint control for flexible joint robots (FJR) stochastic system. First, by combining the command filtered backstepping method with FT control, not only does it solve the “explosion of complexity” problem, but it also ensures that the error of the FJR stochastic system converges in FT. Second, the asymmetric time-varying output constraint problem of FJR stochastic system is solved by designing a nonlinear transformation function (NTF) only depends on the system output, which reduces the difficulty of system stability analyses and relaxes the constraints on the initial value of the output. Third, by exploiting the fuzzy logic system, the adverse effect of the unknown stochastic nonlinear disturbances generated by the harmonic drive of the FJR system is effectively overcome. Furthermore, by utilizing the boundary information of dead-zone slopes, the adverse impact of the dead-zone inputs on the efficacy of control is effectively compensated. Finally, the Lyapunov approach is employed to indicate that the signals are convergent, and the simulation results demonstrate the effectiveness of the control algorithm.