Title :
Designing adaptive robust extended Kalman filter based on Lyapunov-based controller for robotics manipulators
Author :
Ghiasi, A.R. ; Ghavifekr, A.A. ; Hagh, Y. Shabbouei ; SeyedGholami, H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Tabriz, Tabriz, Iran
Abstract :
In this paper, a position and velocity estimation method for robotic manipulators which are affected by constant bounded disturbances is considered. The tracking control problem is formulated as a disturbance rejection problem, with all the unknown parameters and dynamic uncertainties lumped into disturbance. Using adaptive robust extended Kalman filter(AREKF) the movement and velocity of each joint is predicted to use in discontinuous Lyapunov-based controller structure. The parameters of the error dynamics have been validated off-line by real data. Computer simulation results given for a two degree of freedom manipulator demonstrate the efficacy of the improved Kalman Filter by comparing the performance of EKF and improved AREKF. Although it is shown that accurate trajectory tracking can be achieved by using the proposed controller.
Keywords :
Kalman filters; Lyapunov methods; adaptive control; manipulators; nonlinear filters; robust control; trajectory control; velocity control; AREKF; adaptive robust extended Kalman filter; bounded disturbances; degree of freedom manipulator; discontinuous Lyapunov-based controller structure; disturbance rejection problem; dynamic uncertainties; error dynamics parameters; joint movement; joint velocity; position estimation method; robotic manipulators; tracking control problem; trajectory tracking; velocity estimation method; Joints; Kalman filters; Manipulator dynamics; Robustness; Uncertainty; Adaptive robust extended Kalman filter; Kalman filter; Robotic Manipulators; Tracking Problem;
Conference_Titel :
Modeling, Simulation, and Applied Optimization (ICMSAO), 2015 6th International Conference on
Conference_Location :
Istanbul
DOI :
10.1109/ICMSAO.2015.7152248