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With the study on the constructive method of generic functional link artificial neural network(FLANN), a novel constructive method based on the least squares support vector machines (LS-SVM) is proposed and applied to building the nonlinear object model and inverse model. The nonlinear system identification technology of this method is applied to the adaptive inverse control to increase the self-adaptability...
In this paper a new simple, three-parameter nonlinear mathematical model is proposed to represent the nonlinear characteristics of the power amplifier/loudspeaker nonlinearity in acoustic echo cancellers. The three parameters of the model are directly related to three distinct different sections of the nonlinear characteristic. The model and its first derivatives are continuous and stretch over the...
Open-channels networks used for water distribution are subject to algal developments that can induce major disturbances such as clogging issues on hydraulic devices (pipes, weirs, filters,...). We already studied the use of flushes to manage these algae developments. The flush is carried out by increasing the hydraulic shear conditions using the hydraulic structures of the canal network. In response...
Nanotechnology is more and more attracting worldwide attention and is deemed to be one of the major future technologies, especially in medical sciences. For medical use, Nanoparticles (NPs) offer a wide spectrum of applications since they seem to be able to move through organic tissue without barriers. This can be beneficial on the one hand and can bear risks on the other. Nanotoxicity research has...
The Leaky Integrate and Fire (LIF) model of a neuron is one of the best known models for a spiking neuron. A current limitation of the LIF model is that it may not accurately reproduce the dynamics of an action potential. There have recently been some studies suggesting that a LIF coupled with a multi-timescale adaptive threshold (MAT) may increase LIF's accuracy in predicting spikes in cortical neurons...
Due to the ability of malicious worms to spread quickly over the Internet, detection and reaction mechanisms are needed in order to stop the progress of the infection process. Existing worm thwarting techniques do not take into account the false negative and false positive probabilities when implementing the responses. In this paper, we study the impact of the efficiency of the worm detection process...
This paper presents a self-tuning adaptive control structure designed through the minimization of a criteria function. It is described the computation methodology of the control law, being particularized for the case of a dual winding induction generator's excitation control. The parameter's estimator, integrated into the control system, is based on the online least mean square error algorithm. In...
This paper deals with an online identification of the Generalized Maxwell Slip (GMS) friction model for both presliding and sliding regime at the same time. This identification is based on robust adaptive observer without friction force measurement. To apply the observer, a new approach of calculating the filtered friction force from the measurable signals is introduced. Moreover, two approximations...
Semantic interoperability problems have found their solutions using languages and techniques from the Semantic Web. The proliferation of ontologies and meta-information has improved the understanding of information and the relevance of search engine responses. However, the construction of semantic graphs is a source of numerous errors of interpretation or modeling and scalability remains a major problem...
This paper presents a simulated Model Reference Adaptive Controller (MRAC) and its application to regulate steam temperature in distillation process for essential oil extraction system. Steam temperature is one of the most significant parameters that can influence the composition of essential oil yield in terms of quality and quantity. Due to parameter variations and changes in operation conditions...
This paper investigates the characteristic modeling method for multi-variable linear time invariant systems. To characterize the dynamic information, the multi-variable linear time invariant system is transformed to a Jordan normal form. Then, a characteristic model is developed based on the Jordan normal form. The resulting characteristic model is a second-order difference equation, all the dynamic...
An Unmanned Surface Vehicle for bathymetry is introduced. Based on fluid dynamic of the USV, its three-degree of freedom motion model is constructed. The heading error is used for the motion model's feedback variable, and waypoint tracking is achieved by the Line-Of-Sight algorithm. In the adaptive isobath tracking, an oscillating motion of USV is defined firstly, which can be implemented by waypoint...
A method of quantitative contribution assessment of power source in critical branch is proposed in this paper. During the various operation modes, a branch must keep its power flow within the critical boundary. A simple branch model is given to represent the overhead line, cable or transformer. The index proximity of criticality (IPC) is formulated to evaluate the severity. An electrical decomposition...
This paper the dynamic model of multi-input and single-output is established, which takes the coal feed and water feed as the inputs and the main steam temperature as the output. Adaptive Network-based Fuzzy Inference System (ANFIS) is used to establish the system model, and using the field data on the identification and checking of model. The results show that the output of identification is consistent...
In this paper, an identification method for dynamic hysteresis based on Duhem model is proposed. In this method, the functions involved in the Duhem model is approximated by polynomials based on the well-known Weierstrass theorem. Then, the general solutions to approximate the functions in the model are derived. The recursive least squares method is implemented to estimate the coefficients of the...
For the tracking control problem of vehicle suspension system, a method of adaptive sliding mode control is derive in this paper. The influence of parameter uncertainties and external disturbances on the system performance can be reduced and control robustness can be improved. The adaptive sliding mode controller is designed so that the practical system can track the state of the reference model....
This paper discusses on the adaptive neural network model for predicting the energy consumption at a metering station. The function of the metering system is to calculate the energy consumption of the outgoing gas flow. To ensure the robustness of the developed model, it is suggested to make the model an adaptive model that will periodically update the weights. This will ensure the reliability of...
In this paper the Biological Immune System is considered and a model based on Immune System behavior is proposed. For simulation of proposed model, agent's structure and the Multi Agent System are established based on the Capra Model. To implement the proposed model we used reaction agents in Netlogo environment. Finally the effects of learning, adaptation and interaction capabilities in system robustness...
In this paper, the performance of the traditional linear current-loop strategy of a single-point Electromagnetic suspension system is analyzed and its disadvantages in application is pointed out. It is concluded that the time constant of the resultant voltage-current subsystem varies as the changes of the suspension states, which will destroy the condition of implementing model reduction by the method...
A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore,...
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