TY - GEN
T1 - Adaptive Control of Robotic Arm-Based Motion Cueing System Considering Phase Restrictions
AU - Andrianova, Olga
AU - Chairez, Isaac
AU - Poznyak, Alexander
AU - Sanchez, Alejandra Hernandez
AU - Mireles, Caridad
AU - Chertopolokhov, Viktor
AU - Bugriy, Grigory
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - A novel controller for solving the acceleration tracking of an end-effector of a multi-articulated robotic manipulator is proposed in this study, including the actuator dynamics as part of the control design. The controller possesses state dependent gains that include the presence of states restrictions in angular displacements and velocities for the robot joints. The design of the state-dependent gains is developed using a class of logarithmic barrier Lyapunov functions with time-varying parameters that are evolving using the state restrictions information. A back-stepping strategy leads to defining the design of the voltage that drives the actuators to complete the acceleration tracking when it is feasible considering the complementary joints restrictions. The proposed controller is numerically evaluated using a virtual representation of six degrees of freedom industrial robot. The obtained trajectories for acceleration of the end-effector show the effective tracking of the reference acceleration, while the joints position and velocities restrictions are satisfied. The second set of evaluations confirm that under some non-feasible reference accelerations, the joints restrictions are satisfied. The comparison with traditional non-restricted state feedback confirmed the superiority of the proposed controller, measured in terms of the mean square error of the acceleration tracking and the satisfaction of the joint restrictions.
AB - A novel controller for solving the acceleration tracking of an end-effector of a multi-articulated robotic manipulator is proposed in this study, including the actuator dynamics as part of the control design. The controller possesses state dependent gains that include the presence of states restrictions in angular displacements and velocities for the robot joints. The design of the state-dependent gains is developed using a class of logarithmic barrier Lyapunov functions with time-varying parameters that are evolving using the state restrictions information. A back-stepping strategy leads to defining the design of the voltage that drives the actuators to complete the acceleration tracking when it is feasible considering the complementary joints restrictions. The proposed controller is numerically evaluated using a virtual representation of six degrees of freedom industrial robot. The obtained trajectories for acceleration of the end-effector show the effective tracking of the reference acceleration, while the joints position and velocities restrictions are satisfied. The second set of evaluations confirm that under some non-feasible reference accelerations, the joints restrictions are satisfied. The comparison with traditional non-restricted state feedback confirmed the superiority of the proposed controller, measured in terms of the mean square error of the acceleration tracking and the satisfaction of the joint restrictions.
KW - acceleration tracking
KW - back-stepping strategy
KW - barrier Lyapunov functions
KW - robotic manipulator
KW - state restrictions
UR - http://www.scopus.com/inward/record.url?scp=85134265543&partnerID=8YFLogxK
U2 - 10.1109/STAB54858.2022.9807581
DO - 10.1109/STAB54858.2022.9807581
M3 - Contribución a la conferencia
AN - SCOPUS:85134265543
T3 - Proceedings of 2022 16th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference), STAB 2022
BT - Proceedings of 2022 16th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference), STAB 2022
A2 - Tkhai, Valentin N.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Stability and Oscillations of Nonlinear Control Systems (Pyatnitskiy's Conference), STAB 2022
Y2 - 1 June 2022 through 3 June 2022
ER -