Modeling And Control Of 2-degree-of-freedom Manipulator

In recent years,due to the loss of population dividends,China is leading the transformation of economic development actively,then the domestic labor-intensive low-end manufacturing industry is gradually transforming into technology-intensive high-end manufacturing.Hence,the demands of high degree of automation are growing,which drives the rapid development of robot research.With the continuous development of the robot industry,the performance requirements of the robot are getting higher and higher,and the dynamic control of the robot has become an effective method to solve the problem of inaccuracy in the robot trajectory tracking and become a research hotspot.In this thesis,the dynamic motion control for robotic systems is studied.By applying the adaptive control strategy and the unknown input observer to robotic systems,three kinds of control strategies are proposed(1)Robust adaptive control of manipulator.By introducing the filter operation and including a new leakage term in the adaptive law,a robust adaptive control method of the manipulator is proposed to guarantee the parameter estimation.The analysis shows that the algorithm can realize the convergence of parameter estimation error and tracking error,simultaneously.(2)Robust adaptive control of bilateral teleoperation system.Further extending our proposed method of adaptive control to the bilateral teleoperation system,we can obtain a robust adaptive control algorithm for bilateral teleoperation system with guaranteed parameter estimation.The stability analysis proves that the proposed control technique can guarantee that the system will realize the parameter error convergence and the master-slave state synchronization even in the presence of communication delay.(3)Precise motion control of manipulator based on unknown input observer.By introducing the filter transform,an unknown input observer is designed to observe the lumped external disturbances and unmodeled dynamics,and the observed dynamics are taken as a feedforward controller to pre-compensate the disturbances and the unmodeled dynamic.At the same time,we also carry out extensive simulation studies,which show the advantages of the proposed algorithms by comparing them with the traditional control methods.Finally,we use a SCARA(Selective Compliance Assembly Robot Arm)built in our laboratory as the test-rig for experiments,and apply the proposed control algorithms to control this SCARA robot.The experimental results verify the effectiveness of the proposed algorithm and show its potential engineering applications.