We present an alternate controller synthesis method based on a Markovian jump linear system (MJLS) for-

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The article presents the application of a probabilistic robust control scheme for DC-DC Buck Converter, on the basis of the idea of randomly selected scenarios from an uncertain set. This technique involves the analysis of a wide range of control system analysis and design problems for uncertain systems which are amenable to solve the numerical problems in efficient way if the requirements regarding robustness are imposed in probabilistic sense within the paradigm. The output voltage of the converter can be affected by changes in load current. This variation in load appears as a linear uncertain parameter, with a known range, in the dynamic model of the converter. Maintaining the output voltage to the desired value in the presence of load variations is formulated as an LPV H-infinity optimization problem. However, instead of covering the entire uncertainty set using the conventional polytopic approach, we use the scenario based approach to extract the scenarios by explicitly and providing the bound on the number of scenarios, resulting in a design to guarantee an a-priori particular probabilistic robustness in design of control problem for DC-DC Buck Converter. This results in a marginal improvement in transient performance, with regard to overshoot and settling time, of the closed loop system. Numerical simulations are performed to demonstrate the above, and a comparison with the LPV polytopic approach and linear PID control is presented.

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