Dynamic Stability Study On The Novel Controllable Metamorphic Palletizing Robot Mechanism

Metamorphic mechanism is the frontier and hot research field of mechanism. Although great achievements have been made in structural theory and kinematics of mechanism, researches about dynamic stability of metamorphic mechanism are still relatively scarce especially in regard to dynamic stability study on task-oriented controllable metamorphic mechanism. Moreover, dynamic stability problem about this novel mechanism is a bottleneck for the mechanism widely used in practice.The controllable metamorphic palletizing robot mechanism system which can achieve DOF transform between one DOF and two DOF is investigated in this paper. Constraint condition of nonlinear dynamic model of the mechanism system of all configurations is elicited by kinematics analysis. Stepping motor is selected to drive the input of the mechanism system. Finite element method is applied to build the nonlinear dynamic model of the task-oriented novel controllable metamorphic palletizing robot mechanism system of all configurations. Actual working factors such as mechanism properties, material parameters, control parameters and internal impact excitation that have influence on dynamic property of the mechanism system are taken into consideration in this dynamic model. So steady-state responses of the mechanism system are solved by Newmark method. Based on this calculated dynamic response time series, the largest lyapunov exponent is used as metrics of dynamic stability of the system. Parameters about phase-space reconstruction of this dynamic response time series, time delay and embedding dimension, are figured out by C_C method. And phase space of this dynamic response time series are reconstructed. Then Wolf method is applied to calculate the largest lyapunov exponent of this dynamic response time series. So the changing situation of the dynamic stability of the mechanism system is obtained when the mechanism system is changing configuration. And paths of phase diagrams of the mechanism system output dynamic responses are used to analysis stability of the mechanism system. Finally, genetic algorithm is used for dynamic optimization of the mechanism system. Mathematical optimization model of mechanism properties and material parameters are built. Dynamic property of the mechanism system is improved by optimization calculating as a result.