This article concentrates upon the issue of finite-time tracking control for a category nonlinear systems in pure-feedback form with actuator faults and unmodeled dynamics, where loss effectiveness bias fault are considered. Meanwhile, function approximation method utilizing fuzzy logic dynamic surface approach first-order filter implemented to model unknown terms induced from proposed controll...

The existing uncertainties during the operation of processes could strongly affect performance forecasting systems, control strategies and fault detection systems when they are not considered in design. Because that, study uncertainty quantification has gained more attention among researchers past decades. From this field study, prediction intervals arise as one techniques most used literature ...

In this paper, an adaptive neuro-fuzzy system, called HyFIS, is proposed to build and optimise fuzzy models. The proposed model introduces the learning power of neural networks into the fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training eramples by a ...

We present a novel fuzzy sliding mode control technique for a class of second order dynamical systems based on a piecewise linear sliding manifold. The proposed approach benefits from a reduction in the control action magnitude with respect to classical sliding mode control strategies, enhancing the effectiveness of such strategies under a saturated control input. In addition, employing the pro...

In this study, a fuzzy rule-based optimal controller is designed for nonlinear dynamical systems. The direct second order method (or directdescend-curvature algorithm) with a modification called “modified descend controller (MDC)” is used for calculating the parameters of the fuzzy feedback controller. The optimal control problem defined here has dynamic constraints of nonlinear system states a...

A new approach for analyzing the similarity of dynamical systems is presented with applications to the analysis of voice. This approach is based on a fuzzy information space representation of the trajectories of the voice signal. The similarity between the segments of voice signal is determined based on similarity measures of the corresponding fuzzy information space representation. We present ...

The controllability and the observability of fuzzy dynamical system are studied. The uncertainty of the fuzzy dynamical system is due to the initial condition. The available information on the uncertainty can be described via a membership function. In this paper, we propose a systematic approach to investigate the controllability and the observability of fuzzy dynamical system via the use of th...

Neural and neuro-fuzzy models are powerful nonlinear modelling tools. Different structures, with different properties, are widely used to capture static or dynamical nonlinear mappings. Static (non-recurrent) models share a common structure: a nonlinear stage, followed by a linear mapping. In this paper, the separability of linear and nonlinear parameters is exploited for completely supervised ...