Control Of Robotic Manipulators With Uncertainties Based On Computed Torque

The control problems of robotic manipulators have received great attention in theoretical research and engineering for many years. It is well known that the model-based scheme popularly known as Computed Torque Control (CTC) is effective and its performance is excellent in various control strategies for robotic manipulators. However, the requirements for successfully implementing CTC are fast computation and perfect knowledge of dynamic model. Because CTC is not robust enough in the present of imprecise knowledge of system parameters. In practice, unfortunately, it is impossible to obtain a perfect, or even reasonably accurate dynamic model of a robotic manipulator. Furthermore, the parameters of dynamics model of robotic manipulators may also be subject to change when the manipulator goes about its task. Meanwhile, the system can be influenced by uncertainties such as external disturbance and payload change. Can we say that CTC is invalid in such circumstance mentioned above.In this dissertation, the system of robotic manipulators with entire dynamic model, namely, the robotic system with uncertainties is regarded as controlled plant and the various compensation schemes based CTC are developed on base of the references available.The dissertation gives a brief description about the developing situation and control theory of robot firstly, and then the underlying idea and characteristic of CTC are introduced in detail. Subsequently three classes of control strategies with compensation control structure which are based on CTC are proposed. Namely, Variable Structure Compensation Control(VSCC), Neural Network Compensation Control(NNCC) and Fuzzy Logical Compensation Control (FLCC). The overall idea is that the system of robotic manipulators is decomposed as two parts: one is nominal system with perfect knowledge of dynamic model and the other is system with uncertainties. CTC is used to control nominal system. For uncertainties system, we utilize the regressor of robotic system or bounding function on uncertainties to designdifferent compensation controllers. the outputs of the two parts control the robotic systems together. These proposed control algorithms ensure Global Universe Ultimate Boundedness Stability, Global Asymptotic Stability and Global Exponential Stability of the whole robotic system. The performances of controller such as stability and robustness are analyzed. The simulation results are presented for the same 2-DOF serial robotic manipulator, which validate the effectiveness and feasibility of the proposed schemes. Furthermore, the simulation analysis of CTC plus VSCC is conducted on 6-DOF parallel robot made by our Yanshan University.Besides, a new algorithm for solving the inverse kinematics problem of robotic manipulators is proposed in the dissertation.