ICE is a new incremental construction algorithm of a hybrid system for continuous learning tasks. The basis of the hybrid system is a radial basis function (RBF) network layer. The second layer consists of local models. The two layers are closely combined with a strong interaction. For example information from the model-layer is used by the RBF-layer to decide if new RBF-neurons are needed and ...

A kind of weighted Q-Learning algorithm suitable for control systems with continuous state and action spaces was proposed. The hidden layer of RBF network was designed dynamically by virtue of the proposed modified growing neural gas algorithm so as to realize the adaptive understanding of the continuous state space. Based on the standard Q-Learning implemented by RBF network, the weighted Q-Le...

This paper studies the synchronization of SA and AV Node Oscillators using PSO optimized RBF-based controllers systems. High levels of control activities may excite unmodeled dynamics of a system. This matter changes the rules of controlling the system and achieving an acceptable control performance. In fact, the objective here is to reach a trade-off between tracking performance and parametric...