Research On Coordinate Control For Dual Arm Robots Base On Constrained Optimization

In recent years, the dual arm robots are becoming a research hotspot and bringing much concerned with the development of the robot techniques. However, it is still a challenge to design a dual arm robot controller and make a good tracking in the presence of nonlinear constrains, external disturbances and modeling errors. Therefore, this dissertation makes a deep study on the control problem and the constrains optimization problem for dual arm robot systems, and uses simulation results to demonstrate the effectiveness of the proposed methods.This dissertation firstly builds the kinematics model of a dual arm robot by use the D-H method, and the dynamics model of the manipulators and the manipulated object by use the Lagrange mothed. The internal force model are built by analysis the interaction force between the end-effectors and the manipulated object. Then according to manipulators’model, object’s dynamic model and the internal force model, this dissertation builds the dynamics model of the dual arm robot close chain system.Secondly, this dissertation introduces the basic theory of fuzzy control, and uses the multiple input multiple output fuzzy logic (MIMO) system to approximate a unknown consecutive nonlinear function. Compare with the conventional method, fuzzy logic systems can achieve a good control performance without the prior knowledge of the controlled plant’s precise model and provide an effective tool to design the controller of the robot.Thirdly, this dissertation uses an adaptive fuzzy control mothed to design the controller for the dual arm robot close chain system in the presence of system modeling errors and external disturbances. Then the stability of the system is analyzed by apply the Lyapunov stability theory. The proposed mothed can make the object tracking a reference trajectory in the presence of external disturbances and have good robustness.Finally, this dissertation studies on the dual arm robot with the input nonlinear constrains by use an adaptive inverse and design an adaptive fuzzy controller. The fuzzy logic system combine with the adaptive deadzone inverse can enhance the control precision by the limit the effect of the non-symmetric deadzone. Simulation results demonstrate that the proposed mothed can achieve a good trajectory tracking in the presence of the deadzone constrain and external disturbances. And it also demonstrates that the proposed controller have a good robustness.