In this thesis, end-effector position and orientation tracking problem of a 6 degrees of freedom (DOF) rigid link electrically driven (RLED) revolute joint serial robot manipulator with uncertain parameters and external disturbances is addressed. The system uncertainties and the external disturbances are bounded but their upper limits are unknown. The input matrix, which is always invertible and not necessarily a diagonal matrix, is also assumed to be uncertain with a certain bound. An adaptive sliding mode control (ASMC) is designed to solve tracking problem under the presence of these uncertainties. Note that the designed control method is general, not specific for a 6-DOF RLED revolute joint serial robot manipulator, thus it can be applied to any RLED serial robot manipulators. No regression matrices are required and the uncertainty upper limits are not necessarily known. Furthermore, reducing controller computation time is possible by deliberately considering some parts of the system dynamics and the nth time-derivative reference signals of nth order system, in this case desired joint angular jerk signals, as unknown bounded uncertainties. Lyapunov stability criterion is applied to prove the convergence of the adaptive gain of ASMC, the reaching of the sliding surface, and stability of the system. Besides that, inverse kinematics of the 6-DOF revolute joint serial robot manipulator and trajectory planning of the end-effector between two points in operational space are also designed. The inverse kinematics is developed using geometrical approach, while a fifth order polynomial function is used for the motion law of the trajectory planning. The methods to convert the end-effector translational and rotational velocity, acceleration, and jerk from operational space to joint space are also explained. Finally, simulation results verify the performance of the inverse kinematics, the trajectory planning, and the ASMC.

Keywords: adaptive sliding mode control, inverse kinematics, rigid link electrically driven robot manipulator, trajectory planning

In this thesis, end-effector position and orientation tracking problem of a 6 degrees of freedom (DOF) rigid link electrically driven (RLED) revolute joint serial robot manipulator with uncertain parameters and external disturbances is addressed. The system uncertainties and the external disturbances are bounded but their upper limits are unknown. The input matrix, which is always invertible and not necessarily a diagonal matrix, is also assumed to be uncertain with a certain bound. An adaptive sliding mode control (ASMC) is designed to solve tracking problem under the presence of these uncertainties. Note that the designed control method is general, not specific for a 6-DOF RLED revolute joint serial robot manipulator, thus it can be applied to any RLED serial robot manipulators. No regression matrices are required and the uncertainty upper limits are not necessarily known. Furthermore, reducing controller computation time is possible by deliberately considering some parts of the system dynamics and the nth time-derivative reference signals of nth order system, in this case desired joint angular jerk signals, as unknown bounded uncertainties. Lyapunov stability criterion is applied to prove the convergence of the adaptive gain of ASMC, the reaching of the sliding surface, and stability of the system. Besides that, inverse kinematics of the 6-DOF revolute joint serial robot manipulator and trajectory planning of the end-effector between two points in operational space are also designed. The inverse kinematics is developed using geometrical approach, while a fifth order polynomial function is used for the motion law of the trajectory planning. The methods to convert the end-effector translational and rotational velocity, acceleration, and jerk from operational space to joint space are also explained. Finally, simulation results verify the performance of the inverse kinematics, the trajectory planning, and the ASMC.

Keywords: adaptive sliding mode control, inverse kinematics, rigid link electrically driven robot manipulator, trajectory planning

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