Model-based robot control algorithms require the online evaluation of robot dynamics, leading to hybrid continuous/discrete-time implementations. The performance of these fixed-gain control algorithms varies in the workspace and is not adequate for trajectory tracking. A coherent discrete-time framework for the analysis of model-based algorithms is presented, and predictors to compensate for modeling errors are introduced. The basic controller structure is not altered; an added supervisory module is proposed to monitor performance and adjust the command signal accordingly. Preliminary simulation experiments confirm that one-step-ahead predictors lead to a more uniform performance and are suitable for trajectory-tracking applications.
|Title of host publication||Unknown Host Publication Title|
|Number of pages||6|
|Publication status||Published - Jan 1 1987|
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