Variable–Time–Domain Neighboring Optimal Guidance, Part 1: Algorithm Structure

• Published in: Journal of optimization theory and applications Vol. 166; no. 1; pp. 76 - 92
• Main Authors: Pontani, Mauro, Cecchetti, Giampaolo, Teofilatto, Paolo
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.07.2015; Springer Nature B.V
• Subjects: Algorithms; Applications of Mathematics; Boundary conditions; Calculus of Variations and Optimal Control; Optimization; Computer simulation; Control systems; Control theory; Dynamical systems; Engineering; Gain; Mathematical analysis; Mathematical models; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Optimization algorithms; Studies; Theory of Computation; Trajectories; Optimal space trajectories; Neighboring optimal guidance; Perturbative guidance; 49M05; 2nd-order sufficient conditions for optimality
• ISSN: 0022-3239; 1573-2878
• DOI: 10.1007/s10957-014-0676-6

This paper presents a general purpose neighboring optimal guidance algorithm that is capable of driving a dynamical system along a specified nominal, optimal path. This goal is achieved by minimizing the second differential of the objective function along the perturbed trajectory. This minimization principle leads to deriving all the corrective maneuvers, in the context of a closed-loop guidance scheme. Several time-varying gain matrices, referring to the nominal trajectory, are defined, computed offline, and stored in the onboard computer. Original analytical developments, based on optimal control theory, in conjunction with the use of a normalized time scale, constitute the theoretical foundation for three relevant features: (i) a new, efficient law for the real-time update of the time of flight (the so called time-to-go), (ii) a new termination criterion, and (iii) a new analytical formulation of the sweep method. This new guidance, termed variable–time–domain neighboring optimal guidance, is rather general, avoids the usual numerical difficulties related to the occurrence of singularities for the gain matrices, and is exempt from the main disadvantages of similar algorithms proposed in the past. For these reasons, the variable–time–domain neighboring optimal guidance has all the ingredients for being successfully applied to problems of practical interest.