LEARNING CONTROL FOR TRAJECTORY TRACKING OF NONLINEAR INERTIA WHEEL INVERTED PENDULUM
DOI:
https://doi.org/10.59277/RRST-EE.2023.4.17Keywords:
Nonlinear underactuated system, Iterative learning control algorithm, Stability, Tracking, Maximum absolute of errorsAbstract
This paper proposed the iterative learning control for nonlinear underactuated systems. To improve the convergence speed of iterative learning control for such systems and reduce the fluctuation of the system error, an exponential variable gain D-type closed-loop iterative learning control algorithm was chosen. MATLAB simulation analysis was then performed on an underactuated, nonlinear, and unstable system, namely the inertia wheel inverted pendulum. The simulation results show that the algorithm is effective. Good tracking performance was achieved. The system converges to stable limit cycles after a few iterations, ensuring smooth errors and satisfactory convergence speed.
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