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Efficiently tunable real-time implementation of Riccati equation-based designs: general scheme and benchmark study.

Li-Gang Lin1, Shao-An Kuo2, Ching-Kai Lin3

  • 1Department of Mechanical Engineering, National Central University, Taoyuan, 32001, Taiwan. lglin@g.ncu.edu.tw.

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|July 9, 2026
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Summary

This study enhances real-time computing for state-dependent Riccati equation (SDRE) designs by proposing an FPGA implementation of a Riccati equation solver. This significantly improves computational efficiency and offers tuning flexibility for thrust vector control applications.

Keywords:
Computational enhancementField-programmable gate array (FPGA)Riccati equation (RE)-based designsState-dependent Riccati equation (SDRE)Thrust vector control (TVC)

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Area of Science:

  • Control Systems Engineering
  • Computational Mathematics
  • Aerospace Engineering

Background:

  • Riccati equation (RE)-based designs are computationally intensive for real-time applications.
  • The state-dependent Riccati equation (SDRE) scheme faces challenges due to the high computational burden of solving REs at each time step.
  • Thrust vector control (TVC) is a benchmark application where computational efficiency is critical.

Purpose of the Study:

  • To address the computational burden of SDRE-based designs, particularly for TVC.
  • To develop a computationally efficient and flexible Riccati equation solver for real-time implementation.
  • To guarantee the applicability and asymptotic stability of SDRE-based TVC without relying on extensive numerical checks.

Main Methods:

  • An FPGA hardware implementation of the Structure-Preserving Doubling Algorithm for Riccati equation solving was developed.
  • The extended solver was analyzed for computational efficiency (time and accuracy) and tuning flexibility.
  • The performance was benchmarked against standard MATLAB routines, focusing on computation time and accuracy residuals.

Main Results:

  • The proposed FPGA implementation achieved remarkable computational efficiency in both time and accuracy.
  • The extended solver's computation time was significantly reduced compared to the MATLAB benchmark.
  • Tuning flexibility was provided through the stopping criterion, utilizing the Frobenius norm of the RE's residual matrix.

Conclusions:

  • The FPGA-based Riccati equation solver offers a practical solution to enhance the real-time computational efficiency of SDRE designs.
  • The developed method provides a balance between computational speed and accuracy, crucial for applications like TVC.
  • This approach avoids common compromises by efficiently guaranteeing system stability and applicability.