As energy demand grows globally, the energy management system (EMS) is becoming
increasingly important. Energy prediction is an essential component in the first step to create …

RESULTS AND CHALLENGES OF ARTIFICIAL NEURAL NETWORKS USED FOR
DECISION-MAKING AND CONTROL IN MEDICAL APPLICATIONS Adriana Albu, Page 1 …

Telesurgery has the potential to overcome geographical barriers in surgical care,
encouraging its deployment in areas with sparse surgical expertise. Despite successful in …

This article proposesa control performance standard (CPS)-based fuzzy event-triggered
scheme for load frequency control (LFC) of power systems with a limited communication …

In order to effectively decrease the joint-angular drifts and end-effector position
accumulation errors, a novel adaptive fuzzy recurrent neural network (AFRNN) is proposed …

This paper presents model-free sliding mode controllers and Takagi-Sugeno fuzzy
controllers for the flux and conductivity control of Reverse Osmosis Desalination Plants …

This article studies the fuzzy adaptive output feedback control design problem for nonstrict
feedback multi-input–multi-output nonlinear systems with full-states prescribed performance …

To improve the energy efficiency of a mobile robot, a novel energy modeling method for
mobile robots is proposed in this paper. The robot can calculate and predict energy …

This paper proposes a hybrid controller that consists of a second order data–driven Model–
Free Control (MFC), also known as intelligent proportional–integral (iPI), and a Takagi …

This study aims to develop an adaptive event-triggered estimation sampled-data control
method for a fractional-order permanent magnet synchronous generator (PMSG)-based …