Year: 2025
Type: preprint
Abstract: We present a continuous-time equivalent to the well-known iterative linear-quadratic algorithm including an implementation of a backtracking line-search policy and a novel regularization approach based on the necessary conditions in the Riccati pass of the linear-quadratic regulator. This allows the algorithm to effectively solve trajectory optimization problems with non-convex cost functions, which is demonstrated on the cart-pole swing-up problem. The algorithm compatibility with state-of-the-art suites of numerical integration solvers allows for the use of high-order adaptive-step methods. Their use results in a variable number of time steps both between passes of the algorithm and across iterations, maintaining a balance between the number of function evaluations and the discretization error.
Source: arXiv (Cornell University)
Institution: Czech Technical University in Prague
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4415329053
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