This paper proposes an adaptive approximation-based controller for uncertain strict-feedback nonlinear systems with unknown dead-zone nonlinearity. Dead-zone constraint is represented as a combination of a linear system with a disturbance-like term. This work invokes neural networks (NNs) as a linear-in-parameter approximator to model uncertain nonlinear functions that appear in virtual and act...

Dynamic modelling of biochemical reaction networks has to cope with the inherent uncertainty about biological processes, concerning not only data and parameters but also kinetics and structure. These different types of uncertainty are nested within each other: uncertain network structures contain uncertain reaction kinetics, which in turn are governed by uncertain parameters. Here, the authors ...

The prevailing framework for robust stability and performance analysis requires that the uncertain system be written as a linear fractional transformation of the uncertain parameters. This problem is algebraically equivalent to the problem of deriving the state space realization for a multidimensional transfer function matrix, for which a systematic algorithm was recently provided by Cheng and ...

An adaptive control scheme is developed to study the generalized adaptive chaos synchronization with uncertain chaotic parameters behavior between two identical chaotic dynamic systems. This generalized adaptive chaos synchronization controller is designed based on Lyapunov stability theory and an analytic expression of the adaptive controller with its update laws of uncertain chaotic parameter...

In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the probability distribution of different uncertain parameters. Usually, we can safely linearize the dependence of the desired quantities y (e.g., stress at different structural points) on the uncertain parameters xi – thus enabling...

A new test of robust stability/performance is proposed for linear systems with uncertain real-valued parameters. This test is an extension of the notion of quadratic stability where the xed quadratic Lyapunov function is replaced by a Lyapunov function with aane dependence on the uncertain parameters. Admittedly with some conservatism , the construction of such parameter-dependent Lyapunov func...

we use the basic binomial option pricing method but allow someor all the parameters in the model to be uncertain and model this uncertaintyusing fuzzy numbers. we show that with the fuzzy model we can, with areasonably small number of steps, consider almost all possible future stockprices; whereas the crisp model can consider only n + 1 prices after n steps.

A novel procedure for estimating the relative importance of uncertain parameters of complex FE model is presented. The method is specifically directed toward problems involving high-dimensional input parameter spaces, as they are encountered during uncertainty analysis of large scale, refined FE-models. In these cases one is commonly faced with thousands of uncertain parameters and traditional ...

The problem of service composition is of key importance in the Internet of Things paradigm. A composite Web Service can clearly determine how real life objects described as Web Services could interact with each other. This article proposes a non-functional parameters aggregation algorithm, used in composite service plan optimisation stage, taking into account the uncertainty of the non-function...

1 College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China 2 Department of Armament Engineering, Naval Aeronautical and Astronautical University, Yantai Shandong 264001, China 3 Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai Shandong 264001, China a [email protected], b [email protected], c richkey...