A discrete-time iterative learning control law with exponential rate of convergence

Using basis functions in iterative learning control: analysis and design theory

“…Note that in terminal ILC, the reference signal consists of only one sample. Hillenbrand and Pandit (1999) and Zhang, Wang, Zhou, Ye, and Wang (2008) downsample the i/o signals of the system using time windows to achieve specific convergence properties of the ILC controlled system. In this case, the reference signal is defined using the lower sample rate.…”

Compensation of hysteresis in piezoelectric actuator with iterative learning control

“…Thus, following the existing results [10], if |I N − γL| 2 < 1, e i will be convergent. From the above result, it can be concluded that the choice of the learning gain γ governs the convergence rate.…”

Sensing Parameter Selection Strategy for Ultra-low-power Micro-servosystem Identification

“…The coefficients in (3) and (4) are shown in Table 1. For common commercially available op-amps, e n is roughly inversely proportional to the supply current of the op-amp, I s , as shown in [7] and [9]. Based on the data in [9], the estimated e n with respect to I s is roughly …”

“…Two primary design parameters are fixed measurement sampling rate, for which a higher rate leads to higher power consumption, and sensor noise, for which lower variance requires higher power consumption. Previous studies of sampling rate selection for system identification have indicated that optimal sampling rates exist that minimize the total time required to identify a given set of model parameters [3][4][5][6][7][8] without power constraint. This paper introduces an approach to evaluating those two parameters so as to minimize the expected energy needed to perform system identification of a linear system to a desired error tolerance using a recursive least-squares algorithm.…”