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Output-feedback model predictive control of biological phenomena modeled by S-systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2012 , Conference Paper)
Recent years have witnessed extensive research activity in modeling biological phenomena as well as in developing intervention strategies for them. S-systems, which offer a good compromise between accuracy and mathematical ...
Towards Privacy Preserving Consensus Control in Multi-Agent Cyber-Physical Systems Subject to Cyber Attacks
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Multi-agent systems (MAS) require sharing their information with their neighboring agents to reach a consensus in a distributed manner. In this paper, a transformation-based consensus control methodology is developed and ...
A Bayesian approach for model identification of LPV systems with uncertain scheduling variables
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
This paper presents a Gaussian Process (GP) based Bayesian method that takes into account the effect of additive noise on the scheduling variables for identification of linear parameter-varying (LPV) models in input-output ...
Robust cooperative control reconfiguration/recovery in multi-agent systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2014 , Conference Paper)
In this paper, a reconfigurable control protocol for a linear multi-agent system seeking consensus in presence of actuator faults and saturations and environmental disturbances is investigated. Two controllers, namely the ...
Dynamic performance simulation of an aeroderivative gas turbine using the matlab simulink environment
(
American Society of Mechanical Engineers (ASME)
, 2013 , Conference Paper)
In fossil fuel applications, such as air transportation and power generation systems, gas turbine is the prime mover which governs the aircraft's propulsive and the plant's thermal efficiency, respectively. Therefore, an ...
Application of genetic algorithm in selection of dominant input variables in sensor fault diagnosis of nonlinear systems
(
2013 IEEE International Conference on Prognostics and Health Management, PHM 2013
, 2013 , Conference Paper)
Industrial processes rely heavily on information provided by sensors. Reliability of sensor data is vital to assure an acceptable performance of these complex and nonlinear processes. In this paper, the analytical redundancy ...
Sensor fault detection and isolation of an industrial gas turbine using partial kernel PCA
(
9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2015
, 2015 , Conference Paper)
In this paper, partial kernel principal component analysis (PKPCA) is studied for sensor fault detection and isolation of an aeroderivative industrial gas turbine. Principal component analysis (PCA) is an effective tool ...
Actuator Fault Diagnosis in Multi-Zone HVAC Systems using 2D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
This paper presents a novel supervised on-line fault diagnosis strategy in Heating, Ventilation, and Air conditioning (HVAC) systems for actuator faults using 2D Convolutional Neural Networks. It is based on an efficient ...
Hybrid attack detection framework for industrial control systems using 1D-convolutional neural network and isolation forest
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Industrial control systems (ICSs) are used in various infrastructures and industrial plants for realizing their control operation and ensuring their safety. Concerns about the cybersecurity of industrial control systems ...
Linear parameter-varying control of a copolymerization reactor
(
Elsevier B.V.
, 2015 , Conference Paper)
This paper demonstrates the application of the linear parameter-varying (LPV) framework to control a copolymerization reactor. An LPV model representation is first developed for a nonlinear model of the process. The LPV ...