Optimized LQR Controller Design for Control of MIMO Systems based on Real Coded Genetic Algorithm

Abstract In this work, an optimal linear quadratic regulator (LQR) based controller is designed to control the twin rotor MIMO system (TRMS). To achieve the best possible system performance, the settings of the LQR controller are improved by the use of a real coded genetic algorithm (RCGA). The control of TRMS is a challenging task due to its strong nonlinear characteristics and high cross-coupling effects. This work additionally tests the robustness of the developed controller using the multi-channel output gain and delay margin. This work also tests the developed controller's ability to reject disturbances. The plotted output responses show the efficacy of the designed controller.

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Publication Details

Journal
Research Square
Published
2026-11-11
DOI
https://doi.org/10.21203/rs.3.rs-10794040/v1
Primary Topic
Advanced Control Systems Design
Type
preprint
Controls
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preprint

Optimized LQR Controller Design for Control of MIMO Systems based on Real Coded Genetic Algorithm

Sumit Kumar Pandey
Research Square
Advanced Control Systems Design
preprint

Optimized LQR Controller Design for Control of MIMO Systems based on Real Coded Genetic Algorithm

Sumit Kumar Pandey
preprint en

Abstract

Abstract In this work, an optimal linear quadratic regulator (LQR) based controller is designed to control the twin rotor MIMO system (TRMS). To achieve the best possible system performance, the settings of the LQR controller are improved by the use of a real coded genetic algorithm (RCGA). The control of TRMS is a challenging task due to its strong nonlinear characteristics and high cross-coupling effects. This work additionally tests the robustness of the developed controller using the multi-channel output gain and delay margin. This work also tests the developed controller's ability to reject disturbances. The plotted output responses show the efficacy of the designed controller.

Research Square
Jharkhand Rai University (IN)
Advanced Control Systems Design
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