This paper studies the problem of finite-time (FT) adaptive constraint control for flexible joint robots (FJR) stochastic system. Firstly, by combining the command filtered backstepping method with FT control, not only does it solve the “explosion of complexity”爌roblem, but it also ensures that the error of the FJR stochastic system converges in finite time. Secondly, 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. Thirdly, 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.

中文翻译：

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基于命令过滤器的柔性关节机器人未知死区随机系统的有限时间约束控制


本文研究柔性关节机器人（FJR）随机系统的有限时间（FT）自适应约束控制问题。首先，将命令滤波反步方法与FT控制相结合，不仅解决了“复杂度爆炸”的问题，而且保证了FJR随机系统的误差在有限时间内收敛。其次，通过设计仅依赖于系统输出的非线性变换函数（NTF）解决了FJR随机系统的非对称时变输出约束问题，降低了系统稳定性分析的难度，放宽了对初始值的约束。输出。第三，利用模糊逻辑系统，有效克服了FJR系统谐波驱动产生的未知随机非线性扰动的不利影响。此外，利用死区斜率的边界信息，有效补偿了死区输入对控制效果的不利影响。最后，采用Lyapunov方法表明信号是收敛的，仿真结果验证了控制算法的有效性。