In this paper, the problem of the robust tracking for two-arm condenser cleaning crawler-type mobile manipulators (CCCMM) with delayed angle-velocity uncertainties is original investigated. The two-arm condenser cleaning crawler-type mobile manipulators are composed of a crawler-type mobile platform and two-arm industrial manipulators.The uncertainty is nonlinear time-varying and does not require a matching condition. A wavelet transform and probabilistic neural network (WTPNN) system is used to approximate an unknown controlled system from the strategic manipulation of the model following tracking errors. Based on the Lyapunov method and the linear matrix inequality (LMI) approach, several sufficient conditions, which guarantee the state variables of the closed loop system to converge, globally, uniformly and exponentially, to a ball in the state space with any pre-specified convergence rate, are derived. Experiment results are given to illustrate the superior control performance of the proposed intelligent control method.

本文研究了角速度不确定的两臂冷凝器清洁履带式移动机械手的鲁棒跟踪问题。双臂冷凝器清洗履带式移动机械手由履带式移动平台和双臂工业机械手组成，不确定性是非线性时变的，不需要匹配条件。小波变换和概率神经网络（WTPNN）系统用于根据跟踪误差对模型的战略操纵来近似未知的受控系统。基于Lyapunov方法和线性矩阵不等式（LMI）方法，有几个充分的条件可以保证闭环系统的状态变量全局，全局，均匀和指数收敛，得出具有任何预先规定的收敛速度的状态空间中的球。实验结果表明了该智能控制方法的优越控制性能。