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A new integral type sliding surface (ISM) is design for sampled-data systems for output tracking.
Our result facilitates controller design for sampled-data nonlinear systems via their approximate discrete-time models.
This paper investigates the stability analysis and controller design problems for aperiodic sampled-data control systems.
Tools and insights for the design of sampled-data control systems are derived.
For this, we propose an optimal design via sampled-data H∞ control theory.
Due to this shallow sampling, we applied statistical estimators designed for incompletely sampled data sets to estimate var richness (the total number of var types in the population).
The method is designed for numeric data routinely sampled through a sensor network.
AN drafting the design for data gathering.
A framework called generalized inferential control (GIC) is established for designing robust, linear inferential control systems for multi-rate sampled-data systems.
Hence, an input delay system approach is introduced for sampled-data control design.
It is designed for applications when data samples are received in an online manner in frames.
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