In this paper, a systematic methodology to design fuzzy Takagi-Sugeno observers and controllers will be used to estimate the angular positions and speeds, as well as to stabilise an experimental mechanical system with 3 degrees of freedom (fixed quadrotor). Takagi-Sugeno observers and controllers are compared to observers and controllers based on the linearized model, both designed with the sam...

The problem of intellectual support of initial design stages of complex technical objects is considered. The method, based on construction of approximated fuzzy model (Takagi-Sugeno fuzzy system) using Data Mining methods and following optimization procedure with genetic algorithm is provided.

This paper investigates the application of fuzzy model and generalised predictive control strategy for the construction of a model-based predictive fuzzy controller for non-linear processes. In this method a GPC controller is used with the Takagi Sugeno Kang (TSK) piece-wise fuzzy modeling approach in an adaptive strategy. The developed method is applied to control a continuous stirred tank rea...

This paper is pertained with the problem of admissibility analysis of uncertain discrete-time nonlinear singular systems by adopting the state-space Takagi-Sugeno fuzzy model with time-delays and norm-bounded parameter uncertainties. Lyapunov Krasovskii functionals are constructed to obtain delay-dependent stability condition in terms of linear matrix inequalities, which is dependent on the low...

In this paper, a neural network-driven fuzzy reasoning system for stock price forecast is proposed on the basis of improved Takagi-Sugeno reasoning model. The experimental result shows that the fuzzy neural network has such properties as fast convergence, high precision and strong function approximation ability and is suitable for real stock price prediction.

Analysis and observer design for nonlinear systems have long been investigated, but no generally applicable methods exist as yet. A large class of nonlinear systems can be well approximated by Takagi-Sugeno fuzzy models, for which methods and algorithms have been developed to analyze their stability and to design observers. However, results obtained for Takagi-Sugeno fuzzy models are in general...

The paper presents the possibility of the design of frontal neural networks and feed-forward neural networks (without pre-processing of inputs time series) with learning algorithms on the basis genetic and eugenic algorithms and Takagi-Sugeno fuzzy inference system (with pre-processing of inputs time series) in predicting of gross domestic product development by designing a prediction models wh...

This paper outlines two contributions to stability analysis of fuzzy systems: knowledge of the membership function shape (actually, constraints on the membership function values) and polynomial approaches. Both ideas reduce the conservativeness in the stability analysis of a nonlinear system when expressed as a fuzzy model by using membership shape information and by allowing a more general cla...