Adaptive Neural Networks Based Robust Output Feedback Controllers for Nonlinear Systems

Abougarair, Ahmed J.; Aburakhis, Mohamed; Edardar, Mohamed

doi:10.31763/ijrcs.v2i1.523

Cited by 23 publications

(9 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Feedback system with an adaptive controller. Purpose: load regulation based on the current state of the system and external factors [30,31] (57):…”

Section: Cognitive Modeling (27)mentioning

confidence: 99%

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

Ponomaryova,

Nosov,

Ben

et al. 2024

EEJET

View full text Add to dashboard Cite

The object of this study is the safety control system of ship management, by identifying and restoring the qualification parameters of shipmasters in critical situations. The task solved in the study is the timely determination of an insufficient level of qualification for the performance of certain operations in controlling the movement of the ship, by applying a formal-logical model of detecting the intuitive actions of the operator-shipmaster and gradually restoring his/her qualification parameters using the devised method. The stages of development and the formal-logical structure of the model and method in terms of cognitive automation were described in detail as the study results. It was possible to ensure early detection of risks when controlling the movement of the ship in 56 % of cases, during a laboratory experiment on simulators, which in 24 % of cases turned out to be particularly dangerous. The interpretation of the results involved algorithmizing complex and formalized data on the actions of operators and the application of the method of restoring their qualification parameters, which allowed a comprehensive approach to safety management. The distinguishing features of the findings were to predict the level of danger by simulating maritime operations with input navigational and individual conditions. This made it possible to improve the effectiveness of operations to 89 %, reduce the phenomenon of loss of control over the course to 32 %, reduce critical situations to 7 % and the cost of resources. The scope and conditions of practical use involve a comprehensive assessment of external and internal influences on the level of danger, delay in decision-making by operators, as well as sailing conditions. The simulation results could be used to devise strategies for planning maneuvers, predicting risks, and developing maritime security systems

show abstract

“…Feedback system with an adaptive controller. Purpose: load regulation based on the current state of the system and external factors [30,31] (57):…”

Section: Cognitive Modeling (27)mentioning

confidence: 99%

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

Ponomaryova,

Nosov,

Ben

et al. 2024

EEJET

View full text Add to dashboard Cite

show abstract

“…For example, if the BG_Level is high and the BG_Rate is positive, the output would suggest a higher dosage (H or VH) to bring down the blood glucose level. 24…”

Section: Create Fis1mentioning

confidence: 99%

Artificial pancreas control using optimized fuzzy logic based genetic algorithm

Abougarair,

Abujarir,

Tilamon

2023

IRATJ

View full text Add to dashboard Cite

The aim of this paper is to develop an artificial pancreas that can automate the process of monitoring blood glucose levels and administering insulin to diabetic patients. The device incorporates a fuzzy controller that is optimized through a genetic algorithm and designed using MATLAB. The system comprises three key components: a continuous glucose monitoring (CGM) system, an insulin pump, and the fuzzy controller. The CGM measures blood glucose levels in real-time, and the insulin pump administers insulin doses to maintain blood glucose levels within a specific range. The fuzzy controller adjusts the insulin delivery rate based on the patient's blood glucose levels and their target range. To enhance the system's performance, a genetic algorithm is used to fine-tune the parameters of the fuzzy controller, seeking the optimal set of parameters that minimize the difference between the patient's blood glucose levels and the desired target range. The system is implemented in MATLAB, and simulation results indicate its effectiveness in maintaining blood glucose levels within the desired target range, reducing the risk of hypoglycemia and hyperglycemia. In summary, the proposed artificial pancreas system provides an effective automated solution for monitoring blood glucose levels and administering insulin to diabetic patients, with the fuzzy controller and genetic algorithm optimization enhancing the system's performance.

show abstract

“…The complete details are described below. The plant's NNs model are built during the system identification process, and the system should thereafter be developed or trained utilizing the developed model [72].…”

Section: B Updationmentioning

confidence: 99%

Estimation of Liquid Level in a Harsh Environment Using Chaotic Observer

Shenoy

Venkata

2022

Journal of Robotics and Control

View full text Add to dashboard Cite

The increased demand for liquid level measurement has been a key factor in designing accurate and reliable control systems. Here, a study was carried out to calculate the liquid level in a tank using a pressure sensor for changes in inlet liquid parameters like temperature, density and velocity. Prediction of their variables for the long term is essential due to the randomness present in the input and measurement. Hence, observer design for state estimation of a non-linear dynamic system with uncertainties in the measurement and process becomes important. This work provides a feedback observer solution for a system with multiple inputs and single measurable output. A full state observer model is developed to estimate a system’s states with a sensor placed at a definite position from the pipe’s input point through which the liquid flows at different densities and temperatures. Using the observability properties, Luenberger full state observer is designed by various methods, verified using MATLAB and SIMULINK for the system state estimation. To incorporate process noise and measurement noise, the Kalman estimator is integrated with the system. Chaotic systems are susceptible to initial conditions, variations in parameters and are complex dynamic systems. However, providing consistently precise measurements through particular meters necessitates time-consuming computations that can be reduced by employing machine learning approaches that make use of optimizers. The results obtained are compared with the prediction models obtained using Artificial Neural Networks and are validated through the readings obtained from the experimental setup.

show abstract

Adaptive Neural Networks Based Robust Output Feedback Controllers for Nonlinear Systems

Cited by 23 publications

References 19 publications

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

Devising an approach for the automated restoration of shipmaster’s navigational qualification parameters under risk conditions

Artificial pancreas control using optimized fuzzy logic based genetic algorithm

Estimation of Liquid Level in a Harsh Environment Using Chaotic Observer

Contact Info

Product

Resources

About