An Example of Solving HJB Equations Using Sparse Grid for Feedback Control
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It is well known that solving the Hamilton-Jacobi- Bellman (HJB) equation in moderate and high dimensions (d > 3) suffers the curse of dimensionality. In this paper, we introduce and demonstrate an example of solving the 6-D HJB equation for the optimal attitude control of a rigid body equipped with two pairs of momentum wheels. The system is uncontrollable. To mitigate the curse-of-dimensionality, a computational method based on sparse grids is introduced. The method is causality free, which enjoys the advantage of perfect parallelism. The problem is solved using several hundred CPU cores in parallel. In the simulations, the solution of the HJB equation is integrated into a model predictive control for optimal attitude stabilization.
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Mitigating the Curse of Dimensionality: Sparse Grid Characteristics Method for Optimal Feeback Control and HJB Equations Kang, Wei; Wilcox, Lucas C. (2015-07);We address finding the semi-global solutions to optimal feedback con- trol and the Hamilton–Jacobi–Bellman (HJB) equation. Using the solu- tion of an HJB equation, a feedback optimal control law can be imple- mented in ...
Yan, Hui; Ross, I. Michael; Fahroo, Fariba (The American Institute of Aeronautics and Astronautics (AIAA), 2002-08-15);Feedback solutions to the neighboring optimal control problem are typically obtained by solving the matrix Riccati differential equation. In this paper, we propose a new approach based on solving linear algebraic equations ...
Yan, Hui; Ross, I. Michael; Fahroo, Fariba (The American Institute of Aeronautics and Astronautics (AIAA), 2001-06-25);We develop state feedback control laws for linear time-varying systems with quadratic cost criteria by an indirect Legendre pseudospectral method. This method approximates the linear two-point boundary value problem to a ...