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- W3112013753 abstract "For object controlling in an automatic system with a significant delay that reduces the quality of operation of typical controllers (integral, proportional-integral, proportional-integral-differential), a PI controller with variable or switchable parameters is used which is known for its advantages and belongs to the class of variable-structure controllers (hereinafter referred to as VSC) that do not use the sliding mode. Due to the fact that the selected controller contains switchable parameters, filter and an object with delay is considered, it is extremely hard to use the analytical approaches to parametric optimization of the system. This forces one to turn to algorithmic methods. In the present paper, we use the gradient-based algorithm, in which the components of the gradient are calculated using the sensitivity functions with their known advantages. The generated algorithm for automatic parametric optimization (APO) calculated the optimal parameters of the VSC based on the proximity of the output coordinate of the object to the reference process with a minimum of the integral quadratic criterion. The reliability of the vector of parameterization of the controller found by the generated APO algorithm is confirmed by the necessary and sufficient conditions for the extremum of the selected optimization criterion. The positive experience gained in optimizing the PI controller with variable parameters when using the reference model allows it to be applied to other VSCs that do not use the sliding mode, and so further to expand the practice in the application of the gradient-based algorithm through the sensitivity functions for such a VSC class with given indicatives of transition process quality." @default.
- W3112013753 created "2020-12-21" @default.
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- W3112013753 date "2020-01-01" @default.
- W3112013753 modified "2023-09-23" @default.
- W3112013753 title "Gradient-Based Algorithm for Parametric Optimization of Variable-Structure PI Controller When Using a Reference Model" @default.
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- W3112013753 doi "https://doi.org/10.1007/978-3-030-63319-6_87" @default.
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