On Sampled Control with Distributed Processing
The distributed temporal processing of input and output is the main feature of distributed sampling control (DSC). The DSC method was first used to improve the performance of multi-input multi-output (MIMO) control systems for robots. Control algorithms for which this method can be applied require each system output (or state variable) at a different time point and generate each plant input at a different time point. The purpose of this paper is to introduce the underlying concept and to demonstrate its performance through examples of simple robots operating with model-based controllers. Two controllers are used to drive the same plants. One is based on conventional control principles where feedback signals are simultaneously sampled and plant inputs are applied simultaneously and the other utilizes DSC. Differences in the control action are then analyzed. General aspects of the distributed sampling control are also discussed.
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