In this paper, we present a neural network based control scheme for endeffector path tracking control of a system consisting of a rigid micro manipulator attached at the end of a flexible macro manipulator. The objective is to suppress vibrations in the macro manipulator and at the same time achieve desired motions of the end-effector of the micro manipulator. A two-layer feedforward neural net...

A direct adaptive neural network tracking control scheme is presented for a class of nonaffine nonlinear systems with zero dynamics. The method does not assume boundedness on the time derivative of a control effectiveness term. Parameters in neural networks are updated using a gradient descent method which designed in order to minimize a quadratic cost function of the error between the unknown ...

In this paper, a novel adaptive tracking controller is proposed for mobile robots in presence of wheel slip and external disturbance force based on neural networks with online weight updating laws. The uncertainties due to the wheel slip and external force are compensated online by neural networks in order to achieve the desired tracking performance. The online weight updating laws are modified...

A parameter dependent Riccati equation approach is taken to analyze the stability properties of an output feedback adaptive control law design. The adaptive controller is intended to augment a nominal, fixed gain, observer based output feedback control law. Although the formulation is in the setting of model following adaptive control, the realization of the adaptive controller does not require...

This paper explores an application of support vector regression for adaptive control of an unmanned aerial vehicle (UAV). Unlike neural networks, support vector regression (SVR) generates global solutions, because SVR basically solves quadratic programming (QP) problems. With this advantage, the input-output feedback-linearized inverse dynamic model and the compensation term for the inversion e...

Abstract: This paper presents a robust control method via the intelligent adaptive backstepping design technique for stable walking of nine-link biped robots with unknown model uncertainties and external disturbances. In our control structure, the self recurrent wavelet neural network (SRWNN) which has the information storage ability is used to observe the uncertainties of the biped robots. The...

This paper describes the design and analysis of a proportional integral air speed controller and a nonlinear adaptive dynamic surface altitude controller for the longitudinal dynamics of a generic hypersonic flight vehicle. The uncertain nonlinear functions in the pure feedback flight vehicle model are approximated by using radial basis function neural networks. For the controller design, the c...

A novel robust adaptive fuzzy control (RAFC) algorithm for the permanent magnet (PM) synchronous servomotor drives with uncertain nonlinearities and time-varying uncertainties is presented in this article. Takagi–Sugeno-type fuzzy logic systems are used to approximate uncertain functions. The RAFC algorithm is designed by use of the input-to-state stability (ISS) approach and small gain theorem...

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...