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<p>The authors consider available methods for the optimization of the control of unmanned aerial vehicles (UAVs), which requires the development of more complex control algorithms to improve the performance of rotorcraft UAVs. Using the Python programming language, dynamic optimization of the UAV control system is performed in state space. Integral criteria for minimum control-energy consumption and maximum performance, specified by the corresponding functionals, are used. Using Python, namely the extended SciPy library, the Riccati equation is solved using matrix operations and the eigenvalues of the closed-loop control system are obtained. The main function lqr(A, B, Q, R) of the controller is synthesized using the available SciPy tools. An extended study is conducted to confirm the operability of the developed function.</p>

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Using LQR Controller for Optimizing UAV Control Systems

  • 期刊论文

  • 发表日期：

    2026年1月1日

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  • Yu. K. Taranenko,
  • O. Yu. Oliinyk,
  • V. V. Lopatin

摘要

The authors consider available methods for the optimization of the control of unmanned aerial vehicles (UAVs), which requires the development of more complex control algorithms to improve the performance of rotorcraft UAVs. Using the Python programming language, dynamic optimization of the UAV control system is performed in state space. Integral criteria for minimum control-energy consumption and maximum performance, specified by the corresponding functionals, are used. Using Python, namely the extended SciPy library, the Riccati equation is solved using matrix operations and the eigenvalues of the closed-loop control system are obtained. The main function lqr(A, B, Q, R) of the controller is synthesized using the available SciPy tools. An extended study is conducted to confirm the operability of the developed function.