TY - CHAP
T1 - Adaptive control of the IWP
AU - Moreno-Valenzuela, Javier
AU - Aguilar-Avelar, Carlos
N1 - Publisher Copyright:
© 2018, Springer International Publishing AG.
PY - 2018
Y1 - 2018
N2 - In this chapter, two solutions for the trajectory tracking problem in the IWP using new adaptive algorithms are provided: one neural network-based and the other regressor-based. The design of the new robust algorithms departs from a model-based input–output linearization controller. Then, the control problem is solved, first by means of an adaptive neural network-based controller and second by an adaptive regressor-based controller. An extensive real-time experimental study validates the introduced theory, in which the performance of a classical linear PID controller and the two new adaptive schemes are compared.
AB - In this chapter, two solutions for the trajectory tracking problem in the IWP using new adaptive algorithms are provided: one neural network-based and the other regressor-based. The design of the new robust algorithms departs from a model-based input–output linearization controller. Then, the control problem is solved, first by means of an adaptive neural network-based controller and second by an adaptive regressor-based controller. An extensive real-time experimental study validates the introduced theory, in which the performance of a classical linear PID controller and the two new adaptive schemes are compared.
UR - http://www.scopus.com/inward/record.url?scp=85024095661&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-58319-8_9
DO - 10.1007/978-3-319-58319-8_9
M3 - Capítulo
AN - SCOPUS:85024095661
T3 - Intelligent Systems, Control and Automation: Science and Engineering
SP - 159
EP - 176
BT - Intelligent Systems, Control and Automation
PB - Springer Netherlands
ER -