Quantum-Assisted Barrier Sequential Quadratic Programming for Nonlinear Optimal Control

• URL: http://arxiv.org/abs/2510.18116v1
• Date: Mon, 20 Oct 2025 21:33:44 GMT
• Title: Quantum-Assisted Barrier Sequential Quadratic Programming for Nonlinear Optimal Control
• Authors: Nahid Binandeh Dehaghani, Rafal Wisniewski, A. Pedro Aguiar,
• Abstract summary: We propose a quantum-assisted framework for solving constrained finite-horizon nonlinear optimal control problems.<n>Within this framework, a quantum subroutine is incorporated to efficiently solve the Schur complement step.
• Score: 2.033424698590539
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a quantum-assisted framework for solving constrained finite-horizon nonlinear optimal control problems using a barrier Sequential Quadratic Programming (SQP) approach. Within this framework, a quantum subroutine is incorporated to efficiently solve the Schur complement step using block-encoding and Quantum Singular Value Transformation (QSVT) techniques. We formally analyze the time complexity and convergence behavior under the cumulative effect of quantum errors, establishing local input-to-state stability and convergence to a neighborhood of the stationary point, with explicit error bounds in terms of the barrier parameter and quantum solver accuracy. The proposed framework enables computational complexity to scale polylogarithmically with the system dimension demonstrating the potential of quantum algorithms to enhance classical optimization routines in nonlinear control applications.

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