Advanced control and monitoring of bioprocesses are dependent on accurate state and
parameter information. At the same time, bioprocesses are well known for their time-varying …

Model predictive control (MPC), originally developed in the community of industrial process
control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis …

This paper proposes a novel hybrid learning algorithm with stable learning laws for Adaptive
Network-based Fuzzy Inference System (ANFIS) as a system identifier. The proposed hybrid …

Given a fuzzy logic system, how can we determine the membership functions that will result
in the best performance? If we constrain the membership functions to a certain shape (eg …

Currently, microgrids are frequently used and various control algorithms have been applied
to improve their performance in both grid-connected and islanded modes. However …

This study presents the development of a new filter, the sequential sliding innovation filter
(SSIF), designed for estimating quantities of interest from noisy measurements. The SIF is …

Due to the lack or high costs of measurement devices to monitor and control metabolites in
microbial cultivation processes, state estimators are often required. These estimators …

In this paper, a comprehensive comparison is made of the following sigma-point Kalman
filters: unscented Kalman filter (UKF), cubature Kalman filter (CKF), and the central …

The sliding innovation filter is a newly developed filter that was derived in 2020 to be a
predictor-corrector filter. The filter uses the measurement as a hyperplane, and then applies …

Robotic arms are becoming increasingly popular in industrial applications. However,
improving the response and accuracy of robotic arms while reducing their cost has become …