The combination of model predictive control (MPC) and learning methods has been gaining increasing attention as a tool to systems that may be difficult model. Using MPC function approximator in reinforcement (RL) is one approach reduce the reliance on accurate models. RL dependent exploration learn, currently, simple heuristics based random perturbations are most common. This paper considers va...

In this paper, a new incremental predictive guidance method based on implicit form of velocity to be gained algorithm is proposed. In this approach, the generalized incremental predictive control (GIPC) approach is applied to the linearized model for compensating the guidance error. Instead of using the present state in popular model based predictive controller (MPC), in the new method both pre...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...