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In this paper, we proposed a new method of a fuzzy adaptive controller design for a class of non-affine nonlinear systems in which functions of the systems are unknown. The Lyapunov stability of the closed loop system, robustness against uncertainty and external disturbance, the convergence of the output error to zero and the boundedness of the internal signal are guaranteed. An illustrative example...
This paper presents a decentralized adaptive control design for a class of large-scale nonlinear systems with unknown subsystems. When the subsystems are modeled by affine equations, a direct adaptive controller is devised based on the Lyapunov theory, so that the stability of the closed-loop system is guaranteed by introducing a suitably driven adaptive rule. A neuro-based structure is proposed when...
This paper employs two types of neural networks to control a single-link flexible arm. To train each network, we utilize a gradient-based approach with adaptive learning rate. We first apply the diagonal recurrent neural network (DRNN) to a single-link flexible arm, which is a challenging control problem, in order to investigate the ability of this type of recurrent neural network. We then apply a...
This paper presents a decentralized adaptive controller for a class of large-scale nonlinear systems with unknown subsystems. A direct adaptive controller is devised based on Lyapunov stability analysis so that the stability of the closed loop system is guaranteed by introducing a suitably driven adaptive rule. To show the effectiveness of the proposed decentralized adaptive controller, a nonlinear...
In this paper, the problem of noise rejection for a class of nonaffine nonlinear systems with parameter uncertainty is considered. We develop a neuro adaptive controller with guaranteed stability by introducing a robust adaptive bound based on Lyapunov stability analysis. A radial-basis function type neural network is used in the paper. To show the effectiveness of the proposed controller, the nonlinear...
This paper provides some detailed analysis of the stability of the proposed direct adaptive controller for a special type of nonlinear system based on the previously published papers. The special learning algorithm similar to back propagation provides better stability and wide domain of attraction for the controller provided that the neural network parameters are chosen carefully. The controller acts...
This paper introduces an Evolutionary Computation (EC) based controller and its application to the classical Cart-Pole balancing problem. The paper also provides some detailed analysis of the properties of the proposed controller that belongs to the class of reinforcement based controllers.
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