Multi-model back-stepping sliding mode control of Robotic Manipulators

This paper describes a multiple models controller for robotic manipulators based on combination of SM control and adaptive backstepping control approaches. The robot system working environment is changeful and the robot system operates in multiple environments which may change abruptly from one to another. Therefore, a good way to improve the performance of the controller is to use multiple models control if models are approximately available for different environments. We design a PID performance index with weighting factors and forgetting factors, which make the performance index more real-time. This backstepping controller applied to Robot Manipulator, differs from standard backstepping in that the virtual control inputs are designed based on estimates of the previous virtual control inputs. This eliminates the need to take derivatives of the system dynamics, which simplifies the control law. The design methodology is based on the Lyapunov stability. The simulation results demonstrate the effectiveness and feasibility of the proposed control strategy. PID-type switching index function, which increased forgetting factor making the witching more accurate and reasonable. The simulation results demonstrate the effectiveness and feasibility of the proposed control strategy.