The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper deals with the control of the continuous Takagi Sugeno (TS) fuzzy models using discrete control approach. This approach is structured as follows: first, a discrete model is obtained from the discretization of the continuous TS fuzzy model. In this case, the Euler discretization is used for order of approximation superior to one. Second the gains of a non PDC control law ensuring the stabilization...
Since the beginning of the fuzzy control theory, results have been obtained independently for continuous and discrete models. It is still quite difficult to use nonquadratic Lyapunov functions for the continuous case, while this is much easier for the discrete case. This approach tries to put a bridge between the continuous and discrete cases for the class of continuous Takagi Sugeno fuzzy models...
Since a few years, LMIs conditions associated to the control of continuous Takagi Sugeno (TS) fuzzy models have used non quadratic Lyapunov functions. Indeed they are much more general than classical quadratic functions. However, there are requirements about the derivative of the membership functions appearing in the LMIs. Whereas, this problem doesn't exist with discrete time models. This study tries...
This paper proposes a new method to stabilize the continuous-time TS fuzzy models by using results from their discretized models. The proposed approach is structured as follows: first, a discrete model is obtained from the discretization of the continuous TS fuzzy model. Second the gains of a non-PDC controller ensuring the stabilization of the discrete model are determined. Third, we check if the...
This paper proposes a new approach which combines unsupervised and supervised learning for training recurrent neural networks (RNNs). In this approach, the weights between input and hidden layers were determined according to an unsupervised procedure relying on the Kohonen algorithm and the weights between hidden and output layers were updated according to a supervised procedure based on dynamic gradient...
For linear plants, IMC have been shown good robustness properties against disturbances and model mismatches. However, when uncertain processes are concerned, the original IMC structure cannot be directly used for control system implementation. In this paper, an internal multiple model control (IMMC) based on linear model's library is introduced. This approach supposes the definition of a set of local...
This paper presents two strategies of nonlinear predictive control based on a Takagi-Sugeno fuzzy model. The first one introduces a fuzzy logic-based modeling methodology, where a nonlinear system is divided into a number of linear subsystems. So the linear model based predictive control (MPC) technique is used for each subsystem. In the second one, the fuzzy model is considered as a nonlinear model...
The important role that mammography is playing in breast cancer detection can be attributed largely to the technical improvements and dedication of radiologists to breast imaging. A lot of work is being done to ensure that these diagnosing steps are becoming smoother, faster and more accurate in classifying whether the abnormalities seen in mammogram images are benign or malignant. In this paper,...
In this paper, a hybrid evolutionary approach, combining the theory of learning automata (LA) and the steady-state genetic algorithm (SSGA), is proposed for design of TSKtype fuzzy model (TFM). In the proposed memetic approach, both the number of fuzzy rules and adjustable parameters in the TFM are designed concurrently. A learning automaton, which systematically updates a strategy to enhance the...
The important role that mammography is playing in breast cancer detection can be attributed largely to the technical improvements and dedication of radiologists to breast imaging. A lot of work is being done to ensure that these diagnosing steps are becoming smoother, faster and more accurate in classifying whether the abnormalities seen in mammogram images are benign or malignant. This paper takes...
This paper presents the stability analysis of parameter identification. The Takagi Sugeno fuzzy model is employed to represent the discrete time nonlinear dynamical systems. Once the structure of the fuzzy model is fixed, the parameters can be optimized. The parameter identification is accomplished by applying the gradient method where the iteration rates are specific to each parameter. The stability...
This work discusses how Radial Basis Function (RBF) neural networks can have their free parameters defined by evolutionary algorithms (EAs). For such, it firstly presents an overall view of the problems involved and the different evolutionary approaches used to optimize RBF networks. It also proposes a Memetic (ie. evolutionary algorithms (EAs) augmented with local search) RBF networks (MRBF) that...
The continuous SISO nonlinear system is presented by the Takgi-Sugeno type fuzzy state model. The strategy of reference model direct adaptive control theory is presented then two adaptive fuzzy adjustment algorithms have been proposed. The control law which includes two terms is computed at each sampling time. The single synchronous generator coupled to the infinite-bus power system is used to check...
This work consists on the evaluation of the performances of three neural classifiers. The Multi-Layer Perceptron (MLP), the Self-Organizing Map (SOM), the Learning Vector Quantization (LV Q) are considered by this study. The example that will be considered in the evaluation of the technical classifications's performances is the handwritten character recognition.
This paper presents a design method of robust fuzzy PID controller for discrete-time uncertain nonlinear systems. The Takagi-Sugeno fuzzy model with parameter uncertainties is employed to describe discrete-time uncertain nonlinear system with bounded uncertainties. A robust pole placement called pole coloring is used to control each local model. Controller parameters are determined through cost function...
In this paper, a new constructive training algorithm for feed forward MLP neural networks has been developed for isolated word recognition. An incremental training procedure has been employed where the training patterns are learned incrementally, i.e one by one. This algorithm started with a single training pattern and a single hidden-layer using one neuron. During neural network training, the hidden...
In this paper, a new approach for neural PID tuning is presented based on the use of a neural network and the internal model control (IMC) principle. The neural network is used to adjust on line the PID controller after an off line training step. The developed approach is based on the use of a neural supervisor having as inputs the control signal, its correspondent output and the filter time constant...
This paper presents a new learning algorithm for feedforward neural networks. This algorithm uses the vigilance parameter to generate the hidden layer neurons. This process improves the initial weight problem and the adaptive neurons of the hidden layer. The proposed approach is based on combined unsupervised and supervised learning. In this algorithm, the weights between input and hidden layers are...
An adaptive fuzzy controller is constructed from a collection of fuzzy IF-THEN rules whose parameters are changed or adapted according to adaptive laws for the purpose of controlling a nonlinear plant to track a reference trajectory. The fuzzy adaptive control is composed in two classes: direct and indirect one. The indirect fuzzy adaptive controller will be designed through two steps. The first one...
In this paper, a new SVM (Support Vector Machines) synthesis method is presented. This method is based essentially on training criterion optimization of this machine by a set of hierarchical structures of learning automata. This methodology is adopted for the development of off-line isolated handwritten digits recognition system. A comparison is taken between this new approach and that of a standard...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.