This paper develops an intelligent robust control algorithm for a class of uncertain nonlinear multivariable systems by using a recurrent-cerebellar-modelarticulation-controller (RCMAC) and sliding mode technology. The proposed control algorithm consists of an adaptive RCMAC and a robust controller. The adaptive RCMAC is a main tracking controller utilized to mimic an ideal sliding mode control...

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state...

Robust performance controller design for duty-cycle controlled series resonant converter (SRC) is proposed in this paper. The uncertainties of the converter are analyzed with load variation and power circuit components tolerances are taken into consideration. Additionally, a nominal performance (NP) controller is designed. Closed-loop system is simulated with Orcad and simulation results of r...

an adaptive version of growing and pruning rbf neural network has been used to predict the system output and implement linear model-based predictive controller (lmpc) and non-linear model-based predictive controller (nmpc) strategies. a radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.an unscented kalman filter (ukf) algor...

In this research, first, kinematic and dynamic equations of a 4-DOF 3-link robotic finger are derived using Denavit-Hartenberg convention and Lagrange’s formulation. To model the muscles, several springs and dampers are placed between the finger links. Then, two advanced controllers, namely adaptive-robust and adaptive-neural, which can control the robotic finger in presence of parametric uncer...

Abstrucr-This paper proposes a new direct adaptive control algorithm which is robust with respect to additive and multiplicative plant unmodeled dynamics. The algorithm is designed based on the reducedorder plant, which is assumed to be minimum phase and of known order and relative degree, but is analyzed with respect to the overall plant which, due to the unmodeled dynamics, may be nonmi...

This paper presents an adaptive variable structure controller with on-line identification of the upper bounds of uncertainties and disturbance for MEMS triaxial angular sensors device that is able to detect rotation in three orthogonal axes, using a single vibrating mass. A robust adaptive sliding mode controller is developed and the stability of the closed-loop system can be guaranteed with th...

The DC-DC power converters are widely used; however, the controller design for the DC-DC power converters cannot easily design if the load dynamics vary widely. This paper proposes an adaptive wavelet neural control (AWNC) system for a forward DC-DC power converter. The proposed AWNC system is composed of a neural controller and a robust controller. The neural controller uses a wavelet neural n...

A globally convergent adaptive control scheme for robot motion control with the following features is proposed. First, the adaptation law possesses enhanced robustness with respect to noisy velocity measurements. Second, the controller does not require the inclusion of high gain loops that may excite the unmodeled dynamics and amplify the noise level. Third, we derive for the unknown parameter ...