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Restructuring Controllers to Accommodate Plant Nonlinearities

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Abstract
This thesis explores the possibility of controller restructuring for improved closed-loop performance of nonlinear plants using a gradient based method of symbolic adaptation- Model Structure Adaptation Method (MSAM). The adaptation method starts with a controller which is a linear controller designed according to the linearized model of the nonlinear plant. This controller is then restructured into a series of nonlinear candidate controllers and adapted iteratively toward a desired closed-loop response. The noted feature of the adaptation method is its ability to quantify structural perturbations to the controllers. This quantification is important in scaling the structural Jacobian that is used in gradient-based adaptation of the candidate controllers. To investigate this, two nonlinear plants with unknown nonlinearities viz., nonlinear valve and nonlinear inverted pendulum are chosen. Furthermore, the properties of restructured controllers obtained for two systems, stability, effect of measurement noise, reachability, scalability and algorithmic issues of MSAM are studied and compared with the starting controller.
Type
Thesis (Open Access)
Date
2018-02
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