In this paper, we present an Adaptive Posicast Controller that deals with parametric uncertainties in linear systems with delays. It is assumed that the plant has no right half plane zeros and the delay is known. The adaptive controller is based on the Smith Predictor and Finite-Spectrum Assignment with time-varying parameters adjusted online. A novel Lyapunov-Krasovskii functional is used to s...

This paper presents the application of an adaptive fuzzy logic controller with feed-forward component (AFLCF) to the Selective Compliance Assembly Robot Arm (SCARA Robot). The feed forward torque component is computed on-line using an artificial neural network (ANN) which has been trained off-line. This feed-forward component is designed to deliver the ideal torque component to the robot derive...

In this paper two energy dispatch controllers for use in a grid-independent photovoltaic (PV) system are presented. The first, an optimal energy dispatch controller, is based on a class of Adaptive Critic Designs (ACDs) called Action Dependent Heuristic Dynamic Programming (ADHDP). This class of ACDs uses two neural networks to evolve an optimal control strategy over time. The first neural netw...

This paper proposes a technique for tuning of a discrete adaptive controller that is designed based on Lyapunov stability concepts. The tuning is based on the minimization of a performance index that can be calculated from a generalized eigenvalue problem (GEVP). The resulting controller, tuned with the proposed methodology, provides better performance than an adaptive controller based on a Rec...

Fuzzy model-based adaptive control, unlike traditional fuzzy control, extracts expert knowledge from data by using model identification techniques. In this paper, we propose an analysis of the contradiction in this knowledge as an additional search criterion during the model identification process. In order to do so, we first define a measure of contradiction between fuzzy rules. Then, we assum...

A scheme of direct adaptive H∞ control based on least squares support vector machines (LS-SVM) is proposed for a class of nonlinear uncertain systems. In this method, LS-SVM is employed to construct the adaptive controller, and an on-line learning rule for the weighting vector and bias is derived. A parameter selection method based on the genetic algorithm (GA) is given for LS-SVM regression wi...

Fuzzy model-based adaptive control, unlike traditional fuzzy control, extracts expert knowledge from data by using model identification techniques. In this paper, we propose an analysis of the contradiction in this knowledge as an additional search criterion during the model identification process. In order to do so, we first define a measure of contradiction between fuzzy rules. Then, we assum...

There are some experiences that researcher come across quite number of time for very large networks in the initial samples such that they cannot finish the sampling procedure. Two solutions have been proposed and used by marine biologists which we discuss in this article: i) Adaptive cluster sampling based on order statistics with a stopping rule, ii) Restricted adaptive cluster sampling. Until...