This paper presents a comparative analysis of well-known state estimation methods that are commonly used in real systems. The aim of this research is to measure and then evaluate the robustness (i.e., a measure of performance when a small and deliberate changes are made to the method conditions) of these methods against modeling uncertainties. The state… (More)
This paper presents the application of the new developed second-order Smooth Variable Structure Filter, 2<sup>nd</sup>-order SVSF, for fault detection under uncertain conditions. The 2<sup>nd</sup>-order SVSF is a novel modelbased state estimation method formulated in a predictor-corrector form. It produces robust state estimation under uncertain… (More)
The optimal pump scheduling allows for computing the most economical energy costs and provides more efficient operations for complex water distribution systems (WDS) with multiple pumping stations. The proposed technique employs the latest advances in multi-agent Particle Swarm Optimization (MOPSO) to automatically determine the most cost-effective… (More)
In this paper, we describe an adaptive technique for states and parameter estimation involving a combination of two methods, namely the Variable Structure Filter (VSF) and the Extend Kalman Filters (EKF).