A robust optimal controller for the Ward-Leonard system in a wind turbine is used to meet the performance and stability requirements when the system parameters change. However, designing according to the robust optimal method often leads to a high-order controller. This study investigated the application of order reduction algorithms to simplify the controller and help it better meet the real control problem. Comparative evaluation of the order reduction controller methods showed that the second-order reduction controller according to Moore's balanced truncation algorithm was the most suitable to replace the higher-order controller. The step response quality of the system was better when using a second-order reduction controller than a higher-order controller.
This paper presents a method for using a model reduction algorithm to design low-order digital filters. Designing an IIR digital filter that meets the specifications often leads to a high-order digital filter. To reduce the computation time and increase the response rate of the filter, we need to reduce the order of the high-order digital filter. Applying the LQG balanced truncation algorithm to reduce the demand for high-order digital filters shows that low-order filters can completely replace high-order digital filters. The simulation results show that the use of the LQG balanced truncation algorithm in order to reduce the filter order is correct and efficient.
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