In this paper, an observer-based direct adaptive fuzzy-neural network (FNN) controller with supervisory mode for a certain class of high order unknown nonlinear dynamical system is presented. The direct adaptive control (DAC) has the advantage of less design effort by not using FNN to model the plant. By using an observer-based output feedback control law and adaptive law, the free parameters o...

Normal industrial PD control of robot has two drawbacks, it needs joint velocity sensors; it cannot guarantee zero steady state error. In this paper we make two modifications to overcome these problems. High-gain observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate gravity and friction. We give a new proof for high-gain observer, which explains a ...

An adaptive robust controller is introduced for high-precision tracking control problems of robotic manipulators with output constraints. A nonlinear function employed to transform the constrained objective new free variables that are then synthesized using a sliding-mode-like as an indirect mission. signal derived ensure boundedness main without violation physical The performance improved by a...

In this paper, we investigate the problem of Neural Network (NN) observer for nonlinear systems. Therefore, it can be applied to systems with higher degree of nonlinearity with any a priory knowledge about system dynamics. The proposed neuro-observer is a three-layer feedforward neural network, which is trained extensively with the error backpropagation learning algorithm including a correction...

Abstract: This paper presents a neuro-adaptive output-feedback stabilization method for nonlinear non-minimum phase systems with partially known Lipschitz continuous functions in their arguments. The proposed controller is comprised of a linear, a neuro-adaptive, and an adaptive robustifying control term. The adaptation laws for the neural network weights are obtained using the Lyapunov’s direc...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...