Iterative Learning Control with Feedback Using Fourier Series with Application to Robot Trajectory Tracking

퓨리에 급수 근사를 이용한 궤환을 가진 반복 학습제어와 로보트 궤적 추종에의 응용

The Fourier series are employed to approximate the input/output(I/O) characteristics of a dynamic system and, based on the approximation, a new learing control algorithm is proposed in order to find iteratively the control input for tracking a desired trajectory. The use of the Fourier approximation of I/O renders at least a couple of useful consequences: the frequency characteristics of the system can be used in the controller design and the reconstruction of the system states is not required. The convergence condition of the proposed algorithm is provided and the existence and uniqueness of the desired control input is discussed. The effectiveness of the proposed algorithm is illustrated by computer simulation for a robot trajectory tracking. It is shown that, by adding feedback term in learning control algorithm, robustness and convergence speed can be improved.