Search results for "Adaptive"
showing 10 items of 792 documents
Adaptive type-2 fuzzy control of non-linear systems
2009
The paper describes the development of two different type-2 adaptive fuzzy logic controllers and their use for the control of a non linear system that is characterized by the presence of bifurcations and parameter uncertainty. Although a type-2 fuzzy logic controller is able to handle the non linearities and the uncertainties present in a system, its robustness and effectiveness can be increased by the use of an opportune adaptive algorithm. A simulation study was conducted to compare the behavior of adaptive controllers with that of simple type-1 and type-2 fuzzy logic controllers. The system to be controlled, used for the simulation, is a continuous bioreactor for the treatment of mixed w…
Adaptive type-2 fuzzy logic control of a bioreactor
2010
Two adaptive type-2 fuzzy logic controllers with minimum number of rules are developed and compared by simulation for control of a bioreactor in which aerobic alcoholic fermentation for the growth of Saccharomyces cerevisiae takes place. The bioreactor model is characterized by nonlinearity and parameter uncertainty. The first adaptive fuzzy controller is a type-2 fuzzy-neuro-predictive controller (T2FNPC) that combines the capability of type-2 fuzzy logic to handle uncertainties, with the ability of predictive control to predict future plant performance making use of a neural network model of the nonlinear system. The second adaptive fuzzy controller is instead a self-tuning type-2 PI cont…
Nonlinear fuzzy control of a fed-batch reactor for penicillin production
2012
Abstract The process of penicillin production is characterized by nonlinearities and parameter uncertainties that make it difficult to control. In the paper the development and testing of a multivariable fuzzy control system that makes use of type-2 fuzzy sets for the control of pH and temperature are described. The performance of the type-2 fuzzy logic control system (T2FLCS) is compared by simulation with that of a type-1 fuzzy logic control system (T1FLCS) and that of a control system with traditional proportional-integral-derivative (PID) controllers proposed in the literature. The fuzzy controllers are optimized using an ANFIS algorithm. The best results are obtained with the T2FLCS pa…
Adaptive Type-2 Fuzzy Logic Control of Non-Linear Processes
2011
The main objective of this study is to provide a valid and effective approach for the design and development of an adaptive type-2 fuzzy controller (AT2FLC), based on the analysis of the nonlinear process dynamics and the use of an ANFIS technique for the optimization of the controller. The performance of the obtained AT2FLC, characterized by a few number of rules, is higher than the performance of a traditional type-2 fuzzy controller with a larger rule base. The proposed controller is particurarly suitable for the control of processes characterized by uncertainty and time varying parameters.
Dynamic thermal rating for overhead lines: Self-adaptive protection device
2013
The increase in the consumption of electricity, the stringent environmental restrictions and the need to keep costs, make ever more meaningful the need for a flexible operation of existing overhead lines. This paper studies the possibility to use a dynamic thermal rating for overhead line starting from the analysis of the mathematical model and the ability of the latter to reflect the temperature of an overhead conductor in different ambient condition; then it simulates the thermal behaviour of a conductor both in steady state and dynamic one. Finally the paper shows a method for a self-adaptive thermal protection system.
Adaptive Feedback Linearization Control of SynRM Drives With On-Line Inductance Estimation
2023
This article proposes an adaptive input-output Feedback Linearization Control ( FLC ) techniques for Synchronous Reluctance Motor ( SynRM ) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. As a major result, it permits a null stator current steady state tracking error even with a proportional derivative controller. The estimation law is obtained thank…
MRAS Sensorless Techniques for High Performance Linear Induction Motor Drives.
2010
This paper proposes an MRAS (Model reference Adaptive System) speed observer suited for linear induction motors (LIM). Starting from the dynamical equation of the LIM in the synchronous reference frame in literature, the so-called voltage and current models of the LIM in the stationary reference frame, taking into consideration the end effects, have been deduced. These equations have been used respectively as reference and adaptive model of an MRAS observer. As machine under test, a complete dynamic model, based on the constructive elements of the LIM and taking into consideration the end effects by the definition of a proper air-gap function, has been adopted. This model has been previousl…
Adaptive Feed-Forward Neural Network for Wind Power Delivery
2022
This paper describes a grid connected wind energy conversion system. The interconnecting filter is a simple inductor with a series resistor to minimize three-phase current Total Harmonic Distortion (THD). Using the Recursive Least Squares (RLS) Estimator, an online grid impedance technique is proposed in the stationary reference frame using the Recursive Least Squares (RLS) Estimator. An Adaptive Feedforward Neural (AFN) Controller has also been developed using the inverse of the system to improve the performance of the current Proportional-Integral controller under dynamical conditions and provide better DC link voltage stability. The neural network weights are computed in real-time using …
Simulated Annealing Technique for Fast Learning of SOM Networks
2011
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for multidimensional input datasets. In this paper, we present an application of the simulated annealing procedure to the SOM learning algorithm with the aim to obtain a fast learning and better performances in terms of quantization error. The proposed learning algorithm is called Fast Learning Self-Organized Map, and it does not affect the easiness of the basic learning algorithm of the standard SOM. The proposed learning algorithm also improves the quality of resulting maps by providing better clustering quality and topology preservation of input multi-dimensi…
Fast adaptive frame preprocessing for 3D reconstruction
2015
Abstract: This paper presents a new online preprocessing strategy to detect and discard ongoing bad frames in video sequences. These include frames where an accurate localization between corresponding points is difficult, such as for blurred frames, or which do not provide relevant information with respect to the previous frames in terms of texture, image contrast and non-flat areas. Unlike keyframe selectors and deblurring methods, the proposed approach is a fast preprocessing working on a simple gradient statistic, that does not require to compute complex time-consuming image processing, such as the computation of image feature keypoints, previous poses and 3D structure, or to know a prio…