title: Iterative manual control model of human operator.
abstract: In this paper, we present an iterative manual control model of a human operator performing some repetitive task. Various aspects of the model are discussed in detail. Experiments have been done to study the human capability to perform the tasks by learning iteratively. Results of the experiments show the ability of the human operator to perform the tracking of a desired trajectory for some unknown non-linear system with quite reasonable accuracy during the iteration process. It is concluded that the human operator performs the repetitive task by modifying his control action using error and error rate in each iteration. During the modification, the human operator assigns different weights to the error and error rate in each iteration. These results can be implemented in designing more efficient iterative learning control algorithms.
authors.affiliation: Graduate School of Information Sciences, Tohoku University, Aramaki-aza Aoba, Aoba-ku, Sendai 980-77, Japan.
authors.forename: M
authors.initials: M
authors.lastname: Arif
authors.forename: H
authors.initials: H
authors.lastname: Inooka
mesh_terms: D000244:Adenosine Diphosphate; D000465:Algorithms; D003491:Cybernetics; D006801:Humans; D007858:Learning; D008568:Memory; D008954:Models, Biological; D017711:Nonlinear Dynamics; D015203:Reproducibility of Results; D013647:Task Performance and Analysis
chemical_list: D000244:Adenosine Diphosphate