Learning-based Hamilton-Jacobi-Bellman Methods for Optimal Control
Sixiong You,
Ran Dai,
Ping Lu
Abstract:Many optimal control problems are formulated as two point boundary value problems (TPBVPs) with conditions of optimality derived from the HamiltonJacobiBellman (HJB) equations. In most cases, it is challenging to solve HJBs due to the difficulty of guessing the adjoint variables. This paper proposes two learning-based approaches to find the initial guess of adjoint variables in real-time, which can be applied to solve general TP-BVPs. For cases with database of solutions and corresponding adjoint variables of … Show more
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