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An iterative adaptive online fault prognosis via hybrid fuzzy and importance sampling
Proceeding of the 11th World Congress on Intelligent Control and Automation
Year: 2014 | Conference Paper |
This paper discusses new directions of research to detect and diagnose Gaussian and non-Gaussian faults a new nonlinear observer (NOFS) based on Fuzzy and Sequential Important Sampling (FSIS) filter for each unknown states of the plant depending on the diagnosed. The idea based on expanding the size of freedom for the dynamic states of the observers. Therefore, NOFS has been designed and implement...Show More
Fault diagnosis observer via hybrid fuzzy and importance sampling schemes
Proceedings of the 10th World Congress on Intelligent Control and Automation
Year: 2012 | Conference Paper |
This paper introduces a new direction of research to estimate states as well as detect and diagnose (Gaussian and non Gaussian) faults. Therefore, a new observer (FO) has been introduced and designed via a new filter for each output of plant. The new filter FSISF based on Fuzzy and Sequential Important Sampling algorithms to estimate and predicates the. Furthermore, the observer estimates the unkn...Show More
Fault tolerant control for a robust nonlinear robotics via an optimal H∞ scheme
Proceedings of the 10th World Congress on Intelligent Control and Automation
Year: 2012 | Conference Paper |
This paper presents a new optimal Fault tolerant control FTC, which includes anew optimal theorem to design a H∞ controller and new reconfiguration algorithm to reconfigure the controller law. The achieved FTC technique has been applied for Double Two Joints Inverted TJIRA robots arms which raise a plate where the weight of it distributed evenly on the two TJIRA. The study has been carried out dif...Show More
A robust new nonlinear fault tolerant control for robot via an observer
2011 9th World Congress on Intelligent Control and Automation
Year: 2011 | Conference Paper |
Cited by: Papers (5)
To study the properties of the nonlinear robot model and introduce a new adaptive fault tolerant strategy, this paper has been introduced. The adaptive fault tolerant control scheme is designed via two (PID) Proportional -Integral - derivative controllers and a nonlinear observer. The nonlinear model of two inverted robot joints arms on a cart and has been studied and simulated with presence of an...Show More
Fault tolerant control for two collaborative systems using output regulation scheme
Proceedings of the 2010 International Conference on Modelling, Identification and Control
Year: 2010 | Conference Paper |
In this paper a novel collaborative fault tolerant control scheme is presented. To simplify the presentation, only two collaborative subsystems are considered where the state space model is used. To diagnose the faults, adaptive diagnostic observers are used respectively, and the adaptive tuning rule for estimating the faults have been obtained. Based upon the fault diagnosis, a fault tolerant con...Show More
A comparative study of linear observers applied to a DC servo motor
Proceedings of the 2010 International Conference on Modelling, Identification and Control
Year: 2010 | Conference Paper |
Cited by: Papers (2)
This paper presents a comparative study of six different linear observers. The studied observers are Luenberger Observer, Kalman (Filter) Observer, Unknown Input Observer, Augmented Robust Observer, High Gain Observer and Sensitive High Gain Observer. A Matlab simulation of a DC motor model is undertaken to verify the performance of the designed observers. The Comparisons were carried out differen...Show More
A comparative study of nonlinear observers applied to a DC servo motor
2010 8th World Congress on Intelligent Control and Automation
Year: 2010 | Conference Paper |
Cited by: Papers (3)
This paper studies and compares three nonlinear observers (Nonlinear Lyapunov Observer (NLO), Lipschitz Observer (LIO) and Partial Lipschitz Observer (PLIO)) applied to nonlinear model of the DC servo motor. The considered criteria of computations for white noise is the amplitude of the residual and the estimated shape of residual and error probability density functions (PDF) which is estimated by...Show More
An adaptive PI controller for non-Gaussian stochastic systems
2010 8th World Congress on Intelligent Control and Automation
Year: 2010 | Conference Paper |
Cited by: Papers (2)
In this paper, a new algorithm for an adaptive Proportional-Integrator (PI)controller for nonlinear systems subjected to stochastic non-Gaussian disturbance is studied. The minimum entropy control is applied to decrease the closed-loop tracking error under an iterative learning control (ILC) basis. The key issue here is to divide the control horizon into a number of equally time-domain intervals c...Show More
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