This article develops a methodology that enables learning an objective function of optimal control system from incomplete trajectory observations. The is assumed to be weighted sum features (or basis functions) with unknown weights, and the observed data segment states inputs. proposed technique introduces concept recovery matrix establish relationship between any available weights given candid...

We present a learning method to learn the mapping from an input space action space, which is particularly suitable when optimal decision with respect certain unknown cost function. use inverse optimization approach retrieve function by introducing new loss and hypothesis class of mappings. A tractable convex reformulation problem also presented. The effective for input-action in continuous inpu...

the computation of the inverse roots of matrices arises in evaluating non-symmetriceigenvalue problems, solving nonlinear matrix equations, computing some matrixfunctions, control theory and several other areas of applications. it is possible toapproximate the matrix inverse pth roots by exploiting a specialized version of new-ton's method, but previous researchers have mentioned that some...

In this paper, the particular solution technique for inverse simulation applied to the quadrotor maneuvering flight is investigated. The ‎trust-region dogleg (DL) technique which is proposed alleviates the weakness of Newton’s method used for numerical differentiation of system states in the solution process. The proposed technique emphasizes global convergence solution to the inverse simulatio...