a new fault tolerant controller (ftc) has been presented in this research by integrating a fault detection and diagnosis (fdd) mechanism in a nonlinear model predictive controller framework. the proposed fdd utilizes a multi-sensor data fusion (msdf) methodology to enhance its reliability and estimation accuracy. an augmented state-vector model is developed to incorporate the occurred sensor fa...

A new Fault Tolerant Controller (FTC) has been presented in this research by integrating a Fault Detection and Diagnosis (FDD) mechanism in a nonlinear model predictive controller framework. The proposed FDD utilizes a Multi-Sensor Data Fusion (MSDF) methodology to enhance its reliability and estimation accuracy. An augmented state-vector model is developed to incorporate the occurred senso...

The paper presents the development and application of Model Predictive Control (MPC) and Fault Detection and Diagnostics (FDD) technologies to a large-scale HVAC system, their on-line implementation, and results from several demonstrations. The two technologies are executed at the supervisory level in a hierarchical control architecture as extensions of a baseline Building Management System (BM...

The paper presents the development and application of Model Predictive Control (MPC) and Fault Detection and Diagnostics (FDD) technologies to a large-scale HVAC system, their on-line implementation, and results from several demonstrations. The two technologies are executed at the supervisory level in a hierarchical control architecture as extensions of a baseline Building Management System (BM...

Energy simulation programs are increasingly used to assess the energy performance of buildings and heating, ventilation, and air conditioning (HVAC) systems during design. Faults during operation can lead to considerable increase in energy use and associated operating costs. In 2009, 13 of the most common energy faults in U.S. commercial buildings were thought to cause wastes of over $3.3 billi...

nowadays, one-dimensional cutting stock problem (1d-csp) is used in many industrial processes and re-cently has been considered as one of the most important research topic. in this paper, a metaheuristic algo-rithm based on the simulated annealing (sa) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. in this method, the 1d-...

Fast power control is perhaps the most important aspect in a WCDMA system like UTRA-FDD. In this paper, closed loop power control procedures in UTRA-FDD are studied. A physical layer simulator, which has been implemented in the C language from the standard of the UTRA-FDD mode [1]-[4], has been the tool to get the results included in this research. Simulations have been made for different mobil...

The focus of this work is on Statistical Process Control (SPC) a manufacturing process based available measurements. Two important applications SPC in industrial settings are fault detection and diagnosis (FDD). In work, deep learning (DL) methodology proposed for FDD. We investigate the application an explainability concept (explainable artificial intelligence (XAI)) to enhance FDD accuracy ne...

This work presents a toolchain based on the Functional Mockup Interface (FMI) standard for accelarating the adoption of model-based Fault Detection and Diagnostics (FDD) algorithms. The presented toolchain uses nonlinear state estimation techniques to detect multiple simultaneous faults in presence of noisy sensor measurements. The toolchain enables the use of a dynamic model that emulates corr...

This paper presents a new approach to multiobjective optimization by evolutionary algorithm. The approach is based on fuzzification of Pareto dominance relation. Using fuzzy degrees of dominance, a set of vectors (multiple objectives) can be partially ranked. The FDD algorithm, a modification of standard genetic algorithm using this ranking scheme for the selection operations, is presented and ...