Synchronous Control For Multiple Mobile Robotic Manipulator System

With the ever increasing demand for greater productivity,higher-accuracy and more complex task,one single robotic manipulator system cannot satisfy the task requirements.An increasing number of multiple mobile robotic manipulators are employed to carry out some simultaneously tasks in modern manufacturing to reduce work-in-progress.Under the circumstances,it has become a classical topic in system and control domain to deal with the synchronization of MMRMS(multiple mobile robotic manipulator system),which has drawn many attentions from control theory and engineering.MMRMS is a typical uncertainty system with time-variety,highly dynamic nonlinear,strong coupling.The wheeled mobile platform brings nonholonomic constraint and multiple synchronous mobile robotic manipulators increase complexity in control.The key to solve these problems lies two aspects: firstly,combining the wheeled mobile platform with the arm part,establish the kinematics and dynamics model;secondly,design a synchronous controller to make multiple mobile manipulators move in a cooperative manner.This paper selects a simplified model of mobile manipulator as the research object.In the aspect of system model,by analyzing nonholonomic constraint characteristics of the wheeled mobile platform,combing holonomic arm part dynamics model,the uniform dynamics model is established.And then referring to the mathematical model of multiple fixed base robotic manipulators system,dynamics model with system uncertainties of MMRMS is established.In the respects of synchronous control,firstly,trajectory tracking control for single mobile manipulator is researched.Then,directed at multiple fixed base robotic manipulators system with system uncertainties,based on undirected graph theory which describes the information change among the MRMS,a novel distributed leader-follower synchronous control algorithm is developed.To deal with the system uncertainty,robust control strategy is proposed.On the basis of these two aspects,a frame work for RBF neural networks based synchronous control is proposed for MMRMS under leader-follower communication topology.Radial basis function(RBF)neural network enhances estimator and observer are developed to estimate system uncertainty and obtain the leader manipulator's control torque online.An adaptive consensus control algorithm is designed to tune the weight of the RBF neural network.The corresponding stability of the proposed controller is proven by the Lyapunov method.Simulations conducted on a MMRMS indicate the capabilities of the algorithms.