The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical method...

For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storag...

A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor....

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical method...

Dynamic Programming (DP) is an important class of algorithms widely used in many areas of speech and language processing. Recently there have been a series of work trying to formalize many instances of DP algorithms under algebraic and graph-theoretic frameworks. This tutorial surveys two such frameworks, namely semirings and directed hypergraphs, and draws connections between them. We formaliz...

Dynamic Programming (DP) is an important class of algorithms widely used in many areas of speech and language processing. Recently there have been a series of work trying to formalize many instances of DP under algebraic or graph-theoretic frameworks. This report surveys two such frameworks, namely semirings and directed hypergraphs, and draws connections between them. We formalize two particul...

Increasing attention has recently been paid to algorithms based on dynamic programming (DP) due to the suitability of DP for learning problems involving control. In stochastic environments where the system being controlled is only incompletely known, however, a unifying theoretical account of these methods has been missing. In this paper we relate DP-based learning algorithms to the powerful te...

Envelopes are a form of decision rule for monitoring plan execution. We describe one type, the DP envelope, that draws its decisions from a look-up table computed o -line by dynamic programming. Based on an abstract model of agent progress, DP envelopes let a developer approach execution monitoring as a problem independent of issues in agent design. We discuss the application of DP envelopes to...

In this paper, we investigate the numerical solution of discrete time ,infinite horizon,stationary ,discounted Dynamic Programming(DP) problem. We introduce the worst case variant of the standard DP operator and show that it retains the nice properties of the former.We apply this worst case formulation to deterministic systems in continuous space and show that for a class of such systems, any a...

In this paper, the problem of eco-driving for a conventional vehicle equipped with an internal combustion engine is studied. The associated optimal control problem is formulated and solved using Dynamic Programming (DP). The impact of the mesh choice on the optimality of the DP solution is investigated in order to find a trade-off between the optimality of the DP solution and its computation ti...