Adaptive dynamic programming (ADP) is a novel approximate optimal control scheme,
which has recently become a hot topic in the field of optimal control. As a standard approach …

This paper presents a comprehensive survey on application of various conventional,
optimization and artificial intelligence (AI) based computational techniques for impact …

In this article, we introduce some recent research trends within the field of
adaptive/approximate dynamic programming (ADP), including the variations on the structure …

In this paper, the near-optimal control problem for a class of nonlinear discrete-time systems
with control constraints is solved by iterative adaptive dynamic programming algorithm. First …

In this paper, we present a new adaptive dynamic programming approach by integrating a
reference network that provides an internal goal representation to help the systems learning …

In this paper, we apply intelligent optimization method to the challenge of intelligent price-
responsive management of residential energy use, with an emphasis on home battery use …

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent
controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past …

The paper describes a mid-term daily peak load forecasting method using recurrent artificial
neural network (RANN). Generally, the artificial neural network (ANN) algorithm is used to …

This paper compares the performances of a multilayer perceptron neural network (MLPN)
and a radial basis function neural network (RBFN) for online identification of the nonlinear …

Policy iteration approximate dynamic programming (DP) is an important algorithm for solving
optimal decision and control problems. In this paper, we focus on the problem associated …