TY - GEN
T1 - Design and Analysis of Trajectory Tracking Controllers for Noisy 2-Link Robotic Manipulator
AU - Vaishnavi, J.
AU - Singh, Bharat
AU - Kumar, Rajesh
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In the real world, the tracking controllers designed for ideal scenarios will be inaccurate due to presence of noise. This paper deals with trajectory tracking control of a two-link manipulator using three different tracking controllers namely, Proportional Integral Derivative (PID), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Back-stepping controller in a noisy environment. Here, the PID controller is designed using the singular perturbation technique, it helps in dealing with external noise. However, its performance is not good with variable noise. Thus, the ANFIS controller is developed in which the rules are based on data collected from previously designed PID controller. Lastly, the back-stepping controller based on the virtual control signal using Lyapunov for zero error tracking is developed. The three controllers for the manipulator have been tested with the introduction of variable random noise and a fixed noise quantity. Performance analysis of these controllers is based on ISE (Integral Square Error), IAE (Integral Absolute Error), ITSE (Integral Time Squared Error), and ITAE (Integral Time Absolute Error). The simulation results illustrate the accuracy of the ANFIS controller which has better tracking in comparison to the other two control schemes with comparable torque inputs.
AB - In the real world, the tracking controllers designed for ideal scenarios will be inaccurate due to presence of noise. This paper deals with trajectory tracking control of a two-link manipulator using three different tracking controllers namely, Proportional Integral Derivative (PID), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Back-stepping controller in a noisy environment. Here, the PID controller is designed using the singular perturbation technique, it helps in dealing with external noise. However, its performance is not good with variable noise. Thus, the ANFIS controller is developed in which the rules are based on data collected from previously designed PID controller. Lastly, the back-stepping controller based on the virtual control signal using Lyapunov for zero error tracking is developed. The three controllers for the manipulator have been tested with the introduction of variable random noise and a fixed noise quantity. Performance analysis of these controllers is based on ISE (Integral Square Error), IAE (Integral Absolute Error), ITSE (Integral Time Squared Error), and ITAE (Integral Time Absolute Error). The simulation results illustrate the accuracy of the ANFIS controller which has better tracking in comparison to the other two control schemes with comparable torque inputs.
KW - ANFIS
KW - back-stepping controller
KW - Multi-Input Multi-Output (MIMO) nonlinear system
KW - noise
KW - PID control
KW - Robotic manipulator
KW - trajectory tracking
UR - http://www.scopus.com/inward/record.url?scp=85126801579&partnerID=8YFLogxK
U2 - 10.1109/ICEECCOT52851.2021.9707933
DO - 10.1109/ICEECCOT52851.2021.9707933
M3 - Conference contribution
AN - SCOPUS:85126801579
T3 - 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques, ICEECCOT 2021 - Proceedings
SP - 544
EP - 549
BT - 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques, ICEECCOT 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques, ICEECCOT 2021
Y2 - 10 December 2021 through 11 December 2021
ER -