Iterative/Repetitive Learning Control: Learning from Theory, Simulations, and Experiments
The reader is referred to the separate encyclopedia entry on iterative learning control (ILC), and to Bien and Xu (1998), Moore and Xu (2000), Ahn et al. (2007). Many control system applications involve executing the same command repeatedly, and returning to the same starting point before starting the next repetition of the command, for example, robots in manufacturing operations. When typical feedback control systems are given a specific time varying command, they produce an output similar to the command, but it is not the same. Also, many control systems are subject to the same external disturbances each repetition. ILC aims to eliminate both of these errors by observing the error measured during the previous run, adjusting the command given in this run, aiming to converge to zero tracking error, or to substantially reduce the tracking error. ILC iteratively learns a command that produces zero...
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- Longman, R. W. (2003). On the interaction between theory, experiments, and simulation in developing practical learning control algorithms. International Journal of Applied Mathematics and Computer Science, 13(1), 101–111.Google Scholar
- Moore, K., & Xu, J.-X. (Guest Eds.) (2000). Special issue on iterative learning control. International Journal of Control, 73(10): 1–999.Google Scholar