Introduction: We discuss the modern ways of developing intelligent problem solvers, focusing on their shortcomings in terms efficiency application for planning purposeful behavior autonomous mobile systems a priori undescribed conditions environment. Purpose: Developing model knowledge representation and processing which would provide to organize activity uncertain Methods: Synthesis frame-like...

In this paper, an approach is introduced which permits a model-free identification and prediction of time-dependent structural behavior. The numerical approach is based on recurrent neural networks for uncertain data. Time-dependent results obtained from measurements or numerical analysis are used to identify the uncertain long-term behavior of engineering structures. Thereby, the uncertainty o...

This paper aims at studying the effect of uncertain parameters on a two-link planar manipulator using a fuzzy logic approach. The uncertain parameters are modeled as fuzzy variables and the dynamic simulation of the robot is performed using fuzzy dynamic analysis. Two case studies are considered to analyze the dynamic behavior of the robot manipulator: a) uncertain payload and b) uncertain payl...

many real time processes have complex, uncertain and nonlinear dynamics. boilers are nonlinear, time varying, multi-input multi-output (mimo) systems, whose states generally vary with operating conditions. the major problem in controlling that system is that its drum water pressure and steam flow dynamics include an integrator that results a critically stable behavior. conventional controller p...

Uncertain data sets have become popular in recent years because of advances in recent years in hardware data collection technology. In uncertain data sets, the values of the underlying data sets may not be fully specified. In this chapter, we will discuss the frequent pattern mining for uncertain data sets. We will show how the broad classes of algorithms can be extended to the uncertain data s...

When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive ‘cost of feedback’, while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the unce...