Abstract: A Fourier series based learning control (FSBLC)
algorithm for tracking trajectories of mechanical systems with
unknown nonlinearities is presented. Two processes are introduced to
which the FSBLC with PD controller is applied. One is a simplified
service robot capable of climbing stairs due to special wheels and
the other is a propeller driven pendulum with nearly the same
requirements on control. Additionally to the investigation of learning
the feed forward for the desired trajectories some considerations on
the implementation of such an algorithm on low cost microcontroller
hardware are made. Simulations of the service robot as well as
practical experiments on the pendulum show the capability of the used
FSBLC algorithm to perform the task of improving control behavior
for repetitive task of such mechanical systems.
Abstract: This paper proposes the designing direct adaptive
neural controller to apply for a class of a nonlinear pendulum
dynamic system. The radial basis function (RBF) neural adaptive
controller is robust in presence of external and internal uncertainties.
Both the effectiveness of the controller and robustness against
disturbances are importance of this paper. The simulation results
show the promising performance of the proposed controller.